chore: @modelcontextprotocol/sdk als Abhängigkeit hinzugefügt

feat: Zusammenfassung der endgültigen Antwort in zwei Schritten umgestaltet
- Zerlegung von `summarizeFinalAnswer` in zwei separate LLM-Aufrufe: 1. Zusammenfassung, Quellen und vorgeschlagene Suchen 2. Anreicherung mit Emojis und HTML-Tags - Verbesserte Prompt-Formulierung für detailliertere Zusammenfassungen - Verwendung eines günstigeren Modells für den Formatierungsschritt - Hinzufügen separater Kostenprotokollierung pro Schritt - Aktualisierung der JSON-Schema-Antwortstruktur
2026-04-05 03:20:20 +02:00 · 2026-04-05 02:04:35 +02:00 · 2026-04-05 01:14:11 +02:00 · 2026-04-05 01:03:04 +02:00 · 2026-04-05 00:53:27 +02:00 · 2026-04-05 00:37:51 +02:00
18 changed files with 1692 additions and 77 deletions
--- a/.gitignore
+++ b/.gitignore
@@ -1,2 +1,3 @@
 node_modules
-.env
+.env
+logs
--- a/README.md
+++ b/README.md
@@ -0,0 +1,99 @@
+# Search Agent
+
+An intelligent search service with REST API, CLI, and MCP server interfaces.
+
+## Features
+
+- **REST API**: Full-featured HTTP API with streaming support
+- **CLI**: Command-line interface for quick searches
+- **MCP Server**: Model Context Protocol server for integration with AI assistants
+
+## Installation
+
+```bash
+npm install
+```
+
+## Usage
+
+### REST API Server
+
+```bash
+npm run serve
+```
+
+The server will start at `http://localhost:3000`.
+
+### CLI
+
+```bash
+npm run search "Your question here"
+```
+
+### MCP Server
+
+```bash
+npm run mcp
+```
+
+## MCP Configuration
+
+To use the search agent as an MCP server in your AI assistant, add this to your configuration:
+
+### Claude Desktop
+
+Add to `claude_desktop_config.json`:
+
+```json
+{
+  "mcpServers": {
+    "search-agent": {
+      "command": "node",
+      "args": ["/path/to/searchAgent/mcpServer.js"],
+      "env": {
+        "EXA_API_KEY": "your-exa-api-key",
+        "OPENROUTER_API_KEY": "your-openrouter-api-key"
+      }
+    }
+  }
+}
+```
+
+### Other MCP Clients
+
+For other MCP clients, configure the command as:
+- Command: `node`
+- Args: `["/path/to/searchAgent/mcpServer.js"]`
+- Environment variables: `EXA_API_KEY` and `OPENROUTER_API_KEY`
+
+## Available MCP Tools
+
+### search
+
+Search for information and return a summarized answer with sources.
+
+**Parameters:**
+- `question` (required): The question or topic to search for
+- `previousClarification` (optional): Previous clarification from the user if the question needed refinement
+- `originalQuestion` (optional): The original question if this is a follow-up
+
+**Example:**
+```json
+{
+  "name": "search",
+  "arguments": {
+    "question": "What are the latest developments in AI?"
+  }
+}
+```
+
+## Environment Variables
+
+Required:
+- `EXA_API_KEY`: Your Exa API key
+- `OPENROUTER_API_KEY`: Your OpenRouter API key
+
+Optional:
+- `PORT`: Port for REST server (default: 3000)
+- `HOST`: Host for REST server (default: 0.0.0.0)
+- `MAINTENANCE_MODE`: Set to "true" to enable maintenance mode
--- a/mcpServer.js
+++ b/mcpServer.js
@@ -0,0 +1,11 @@
+#!/home/seb/.nvm/versions/node/v22.15.1/bin/node
+import dotenv from 'dotenv';
+import { startMCPServer } from './src/mcpServer.js';
+
+// Load environment variables from .env file
+dotenv.config();
+
+startMCPServer().catch((error) => {
+  console.error('Failed to start MCP server:', error);
+  process.exit(1);
+});
--- a/package-lock.json
+++ b/package-lock.json
@@ -9,9 +9,65 @@
      "version": "1.0.0",
      "license": "ISC",
      "dependencies": {
+        "@modelcontextprotocol/sdk": "^1.0.4",
        "@openrouter/sdk": "^0.11.2",
+        "chalk": "^5.6.2",
+        "dotenv": "^17.2.3",
        "exa-js": "^2.11.0",
-        "express": "^5.2.1"
+        "express": "^5.2.1",
+        "tiktoken": "^1.0.22"
+      }
+    },
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+    "node_modules/@modelcontextprotocol/sdk": {
+      "version": "1.29.0",
+      "resolved": "https://registry.npmjs.org/@modelcontextprotocol/sdk/-/sdk-1.29.0.tgz",
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+        "cross-spawn": "^7.0.5",
+        "eventsource": "^3.0.2",
+        "eventsource-parser": "^3.0.0",
+        "express": "^5.2.1",
+        "express-rate-limit": "^8.2.1",
+        "hono": "^4.11.4",
+        "jose": "^6.1.3",
+        "json-schema-typed": "^8.0.2",
+        "pkce-challenge": "^5.0.0",
+        "raw-body": "^3.0.0",
+        "zod": "^3.25 || ^4.0",
+        "zod-to-json-schema": "^3.25.1"
+      },
+      "engines": {
+        "node": ">=18"
+      },
+      "peerDependencies": {
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+      "peerDependenciesMeta": {
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+        "zod": {
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    },
    "node_modules/@openrouter/sdk": {
@@ -37,6 +93,39 @@
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+        "fast-uri": "^3.0.1",
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@@ -99,6 +188,18 @@
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@@ -139,6 +240,23 @@
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+      "license": "MIT",
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@@ -273,6 +426,18 @@
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@@ -316,6 +481,46 @@
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@@ -437,6 +642,15 @@
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+    "node_modules/require-from-string": {
+      "version": "2.0.2",
+      "resolved": "https://registry.npmjs.org/require-from-string/-/require-from-string-2.0.2.tgz",
+      "integrity": "sha512-Xf0nWe6RseziFMu+Ap9biiUbmplq6S9/p+7w7YXP/JBHhrUDDUhwa+vANyubuqfZWTveU//DYVGsDG7RKL/vEw==",
+      "license": "MIT",
+      "engines": {
+        "node": ">=0.10.0"
+      }
+    },
    "node_modules/router": {
      "version": "2.2.0",
      "resolved": "https://registry.npmjs.org/router/-/router-2.2.0.tgz",
@@ -782,6 +1068,27 @@
      "integrity": "sha512-E5LDX7Wrp85Kil5bhZv46j8jOeboKq5JMmYM3gVGdGH8xFpPWXUMsNrlODCrkoxMEeNi/XZIwuRvY4XNwYMJpw==",
      "license": "ISC"
    },
+    "node_modules/shebang-command": {
+      "version": "2.0.0",
+      "resolved": "https://registry.npmjs.org/shebang-command/-/shebang-command-2.0.0.tgz",
+      "integrity": "sha512-kHxr2zZpYtdmrN1qDjrrX/Z1rR1kG8Dx+gkpK1G4eXmvXswmcE1hTWBWYUzlraYw1/yZp6YuDY77YtvbN0dmDA==",
+      "license": "MIT",
+      "dependencies": {
+        "shebang-regex": "^3.0.0"
+      },
+      "engines": {
+        "node": ">=8"
+      }
+    },
+    "node_modules/shebang-regex": {
+      "version": "3.0.0",
+      "resolved": "https://registry.npmjs.org/shebang-regex/-/shebang-regex-3.0.0.tgz",
+      "integrity": "sha512-7++dFhtcx3353uBaq8DDR4NuxBetBzC7ZQOhmTQInHEd6bSrXdiEyzCvG07Z44UYdLShWUyXt5M/yhz8ekcb1A==",
+      "license": "MIT",
+      "engines": {
+        "node": ">=8"
+      }
+    },
    "node_modules/side-channel": {
      "version": "1.1.0",
      "resolved": "https://registry.npmjs.org/side-channel/-/side-channel-1.1.0.tgz",
@@ -863,6 +1170,12 @@
        "node": ">= 0.8"
      }
    },
+    "node_modules/tiktoken": {
+      "version": "1.0.22",
+      "resolved": "https://registry.npmjs.org/tiktoken/-/tiktoken-1.0.22.tgz",
+      "integrity": "sha512-PKvy1rVF1RibfF3JlXBSP0Jrcw2uq3yXdgcEXtKTYn3QJ/cBRBHDnrJ5jHky+MENZ6DIPwNUGWpkVx+7joCpNA==",
+      "license": "MIT"
+    },
    "node_modules/toidentifier": {
      "version": "1.0.1",
      "resolved": "https://registry.npmjs.org/toidentifier/-/toidentifier-1.0.1.tgz",
@@ -926,6 +1239,21 @@
        "webidl-conversions": "^3.0.0"
      }
    },
+    "node_modules/which": {
+      "version": "2.0.2",
+      "resolved": "https://registry.npmjs.org/which/-/which-2.0.2.tgz",
+      "integrity": "sha512-BLI3Tl1TW3Pvl70l3yq3Y64i+awpwXqsGBYWkkqMtnbXgrMD+yj7rhW0kuEDxzJaYXGjEW5ogapKNMEKNMjibA==",
+      "license": "ISC",
+      "dependencies": {
+        "isexe": "^2.0.0"
+      },
+      "bin": {
+        "node-which": "bin/node-which"
+      },
+      "engines": {
+        "node": ">= 8"
+      }
+    },
    "node_modules/wrappy": {
      "version": "1.0.2",
      "resolved": "https://registry.npmjs.org/wrappy/-/wrappy-1.0.2.tgz",
--- a/package.json
+++ b/package.json
@@ -5,15 +5,20 @@
  "type": "module",
  "scripts": {
    "serve": "node restSearch.js",
+    "search": "node searchCLI.js",
+    "mcp": "node mcpServer.js",
    "test": "echo \"Error: no test specified\" && exit 1"
  },
  "author": "",
  "license": "ISC",
  "description": "",
  "dependencies": {
+    "@modelcontextprotocol/sdk": "^1.0.4",
    "@openrouter/sdk": "^0.11.2",
+    "chalk": "^5.6.2",
    "dotenv": "^17.2.3",
    "exa-js": "^2.11.0",
-    "express": "^5.2.1"
+    "express": "^5.2.1",
+    "tiktoken": "^1.0.22"
  }
 }
--- a/public/index.html
+++ b/public/index.html
@@ -289,6 +289,90 @@
            text-decoration: underline;
        }

+        .suggested-searches {
+            display: flex;
+            flex-wrap: wrap;
+            gap: 8px;
+        }
+
+        .suggested-search-btn {
+            padding: 8px 16px;
+            background: #f0f0f0;
+            border: 1px solid #ddd;
+            border-radius: 20px;
+            cursor: pointer;
+            font-size: 0.9rem;
+            transition: all 0.2s;
+            color: #333;
+        }
+
+        .suggested-search-btn:hover {
+            background: #667eea;
+            color: white;
+            border-color: #667eea;
+        }
+
+        /* Cost Breakdown Styles */
+        .cost-breakdown-details {
+            margin-top: 10px;
+        }
+
+        .cost-breakdown-summary {
+            cursor: pointer;
+            font-weight: 600;
+            color: #555;
+            padding: 12px 15px;
+            background: #f8f9fa;
+            border-radius: 6px;
+            border-left: 4px solid #667eea;
+            transition: background 0.2s;
+            list-style: none;
+        }
+
+        .cost-breakdown-summary:hover {
+            background: #e9ecef;
+        }
+
+        .cost-breakdown-summary::-webkit-details-marker {
+            display: none;
+        }
+
+        .cost-breakdown-content {
+            padding: 15px;
+            margin-top: 10px;
+            background: #fff;
+            border: 1px solid #e0e0e0;
+            border-radius: 6px;
+        }
+
+        .cost-table {
+            width: 100%;
+            border-collapse: collapse;
+            font-size: 0.9rem;
+        }
+
+        .cost-table th,
+        .cost-table td {
+            padding: 10px 12px;
+            text-align: left;
+            border-bottom: 1px solid #e0e0e0;
+        }
+
+        .cost-table th {
+            background: #f8f9fa;
+            font-weight: 600;
+            color: #555;
+        }
+
+        .cost-table tr:last-child td {
+            border-bottom: none;
+            font-weight: 600;
+        }
+
+        .cost-table tbody tr:hover {
+            background: #f8f9fa;
+        }
+
        .error {
            background: #fee;
            color: #c00;
@@ -454,16 +538,17 @@
 <body>
    <div class="container">
        <div class="header">
-            <h1>🔍 Search Agent</h1>
+            <h1>🔍 Such-Agent</h1>
        </div>

        <div class="search-section">
            <!-- Example Queries - Moved to top -->
            <div class="example-queries" style="margin-top: 0; padding-top: 0; border-top: none; margin-bottom: 20px;">
                <h3>Beispiel Anfragen:</h3>
-                <button class="example-btn" onclick="setExample('Wie ist die Lage im Iran?')">Lage im Iran</button>
+                <button class="example-btn" onclick="setExample('Wie ist die aktuelle Nachrichten Lage im Iran?')">Lage im Iran</button>
                <button class="example-btn" onclick="setExample('Welche KI Modelle wurden in den letzten Tagen veröffentlicht?')">Neue KI-Modelle</button>
                <button class="example-btn" onclick="setExample('Wie ist das Wetter in Dresden?')">Wetter in Dresden</button>
+                <button class="example-btn" onclick="setExample('Was ist neu in React 19.2?')">React 19.2</button>
            </div>

            <div class="search-box">
@@ -473,26 +558,56 @@
                    id="questionInput" 
                    autocomplete="off"
                >
-                <button class="search-btn" id="searchBtn">Suche</button>
+                <button class="search-btn" id="searchBtn">Suchen</button>
            </div>

            <div class="loading" id="loading">
                <div class="spinner"></div>
-                <p>Searching and analyzing results...</p>
+                <p>Suche und analysiere Ergebnisse...</p>
            </div>

            <div class="error" id="error"></div>

            <div class="results" id="results">
+                 <div class="result-section">
+                    <h2>💡 Vorgeschlagene Folgesuchen</h2>
+                    <div class="suggested-searches" id="suggestedSearches"></div>
+                </div>
+
                <div class="result-section">
-                    <h2>📝 Answer</h2>
+                    <h2>📝 Antwort</h2>
                    <div class="answer" id="answer"></div>
                </div>

                <div class="result-section">
-                    <h2>🔗 Most Relevant Sources</h2>
+                    <h2>🔗 Relevanteste Quellen</h2>
                    <ul class="sources" id="sources"></ul>
                </div>
+
+
+                <!-- Cost Breakdown Section -->
+                <div class="result-section">
+                    <details class="cost-breakdown-details" id="costBreakdownDetails">
+                        <summary class="cost-breakdown-summary">💰 Kostenaufschlüsselung</summary>
+                        <div class="cost-breakdown-content">
+                            <table class="cost-table" id="costTable">
+                                <thead>
+                                    <tr>
+                                        <th>#</th>
+                                        <th>Typ</th>
+                                        <th>Modell</th>
+                                        <th>Eingabe</th>
+                                        <th>Ausgabe</th>
+                                        <th>Kosten (USD)</th>
+                                    </tr>
+                                </thead>
+                                <tbody id="costTableBody">
+                                    <!-- Cost rows will be inserted here -->
+                                </tbody>
+                            </table>
+                        </div>
+                    </details>
+                </div>
            </div>

            <!-- Log Panel -->
@@ -501,9 +616,9 @@
                    <div style="display: flex; align-items: center; gap: 15px;">
                        <div class="connection-status">
                            <span class="status-dot" id="statusDot"></span>
-                            <span id="statusText">Connecting...</span>
+                            <span id="statusText">Verbinde...</span>
                        </div>
-                        <button class="clear-logs-btn" id="clearLogsBtn">Clear</button>
+                        <button class="clear-logs-btn" id="clearLogsBtn">Löschen</button>
                    </div>
                </div>
                <div class="log-container" id="logContainer">
@@ -522,6 +637,7 @@
        const results = document.getElementById('results');
        const answerEl = document.getElementById('answer');
        const sourcesEl = document.getElementById('sources');
+        const suggestedSearchesEl = document.getElementById('suggestedSearches');
        const errorEl = document.getElementById('error');
        const logContainer = document.getElementById('logContainer');
        const statusDot = document.getElementById('statusDot');
@@ -531,14 +647,18 @@
        // SSE connection
        let eventSource = null;
        let logEntries = [];
+        
+        // Clarification state
+        let isAwaitingClarification = false;
+        let clarificationData = null;

        function connectToSSE() {
            eventSource = new EventSource('/stream');
            
            eventSource.onopen = function() {
                statusDot.className = 'status-dot connected';
-                statusText.textContent = 'Connected';
-                addLogEntry('Connected to log stream', 'info');
+                statusText.textContent = 'Verbunden';
+                addLogEntry('Mit Log-Stream verbunden', 'info');
            };
            
            eventSource.onmessage = function(event) {
@@ -572,7 +692,7 @@
            
            eventSource.onerror = function(err) {
                statusDot.className = 'status-dot disconnected';
-                statusText.textContent = 'Disconnected';
+                statusText.textContent = 'Getrennt';
                console.error('SSE Error:', err);
                
                // Attempt to reconnect after 3 seconds
@@ -646,7 +766,7 @@
        async function performSearch() {
            const question = questionInput.value.trim();
            if (!question) {
-                showError('Please enter a question');
+                showError('Bitte geben Sie eine Frage ein');
                return;
            }

@@ -679,10 +799,111 @@
                searchBtn.disabled = false;
            }
        }
+        
+        async function performSearchWithClarification(clarificationText) {
+            if (!clarificationData || !clarificationData.originalQuestion) {
+                showError('Klärungsdaten nicht verfügbar');
+                return;
+            }
+            
+            // Show loading
+            hideError();
+            hideResults();
+            showLoading();
+            
+            try {
+                const response = await fetch('/search', {
+                    method: 'POST',
+                    headers: {
+                        'Content-Type': 'application/json'
+                    },
+                    body: JSON.stringify({
+                        question: clarificationData.originalQuestion + ' ' + clarificationText,
+                        previousClarification: clarificationText,
+                        originalQuestion: clarificationData.originalQuestion
+                    })
+                });
+
+                const data = await response.json();
+
+                if (!response.ok) {
+                    throw new Error(data.error || 'Search failed');
+                }
+
+                displayResults(data);
+            } catch (err) {
+                showError(err.message);
+            } finally {
+                hideLoading();
+            }
+        }

        function displayResults(data) {
+            // Check if clarification is needed
+            if (data.clarificationNeeded) {
+                isAwaitingClarification = true;
+                clarificationData = {
+                    originalQuestion: data.originalQuestion
+                };
+                
+                // Show clarification prompt in the answer area
+                answerEl.innerHTML = `
+                    <div style="background: #fff3cd; padding: 20px; border-radius: 8px; border-left: 4px solid #ffc107;">
+                        <p style="margin-bottom: 15px; font-weight: 600;">${data.fullAnswerHTMLSnippet}</p>
+                        <input 
+                            type="text" 
+                            id="clarificationInput" 
+                            class="search-input" 
+                            style="margin-bottom: 10px;"                        
+                        >
+                        <button 
+                            class="search-btn" 
+                            id="clarificationSubmitBtn"
+                            style="padding: 10px 20px; font-size: 1rem;"
+                        >
+                            Klärung einreichen
+                        </button>
+                    </div>
+                `;
+                
+                // Clear sources since we're waiting for clarification
+                sourcesEl.innerHTML = '<li>Warte auf Klärung...</li>';
+                
+                // Add event listener for clarification submission
+                setTimeout(() => {
+                    const clarificationInput = document.getElementById('clarificationInput');
+                    const clarificationSubmitBtn = document.getElementById('clarificationSubmitBtn');
+                    
+                    if (clarificationInput && clarificationSubmitBtn) {
+                        clarificationInput.focus();
+                        
+                        const handleClarification = () => {
+                            const clarificationText = clarificationInput.value.trim();
+                            if (clarificationText) {
+                                // Search again with the clarification
+                                performSearchWithClarification(clarificationText);
+                            }
+                        };
+                        
+                        clarificationSubmitBtn.addEventListener('click', handleClarification);
+                        clarificationInput.addEventListener('keypress', (e) => {
+                            if (e.key === 'Enter') {
+                                handleClarification();
+                            }
+                        });
+                    }
+                }, 100);
+                
+                showResults();
+                return;
+            }
+            
+            // Reset clarification state for normal results
+            isAwaitingClarification = false;
+            clarificationData = null;
+            
            // Display answer as HTML
-            answerEl.innerHTML = data.fullAnswerHTMLSnippet || '<p>No answer generated</p>';
+            answerEl.innerHTML = data.fullAnswerHTMLSnippet || '<p>Keine Antwort generiert</p>';

            // Display sources
            sourcesEl.innerHTML = '';
@@ -699,10 +920,49 @@
                });
            } else {
                const li = document.createElement('li');
-                li.textContent = 'No sources available';
+                li.textContent = 'Keine Quellen verfügbar';
                sourcesEl.appendChild(li);
            }

+            // Display suggested searches
+            suggestedSearchesEl.innerHTML = '';
+            if (data.suggestedSearches && data.suggestedSearches.length > 0) {
+                data.suggestedSearches.forEach(search => {
+                    const btn = document.createElement('button');
+                    btn.className = 'suggested-search-btn';
+                    btn.textContent = search;
+                    btn.addEventListener('click', () => {
+                        questionInput.value = search;
+                        performSearch();
+                    });
+                    suggestedSearchesEl.appendChild(btn);
+                });
+            } else {
+                suggestedSearchesEl.innerHTML = '<p style="color: #999;">Keine vorgeschlagenen Suchen verfügbar</p>';
+            }
+
+            // Display cost breakdown
+            const costTableBody = document.getElementById('costTableBody');
+            costTableBody.innerHTML = '';
+            if (data.costBreakdown && data.costBreakdown.length > 0) {
+                data.costBreakdown.forEach(item => {
+                    const tr = document.createElement('tr');
+                    tr.innerHTML = `
+                        <td>${item.index}</td>
+                        <td>${item.type}</td>
+                        <td>${item.model || '-'}</td>
+                        <td>${item.prompt_tokens || '-'}</td>
+                        <td>${item.completion_tokens || '-'}</td>
+                        <td>${item.cost}</td>
+                    `;
+                    costTableBody.appendChild(tr);
+                });
+            } else {
+                const tr = document.createElement('tr');
+                tr.innerHTML = '<td colspan="6">Keine Kostendaten verfügbar</td>';
+                costTableBody.appendChild(tr);
+            }
+
            showResults();
        }

--- a/searchCLI.js
+++ b/searchCLI.js
@@ -0,0 +1,76 @@
+import dotenv from 'dotenv';
+import { createClients } from './src/clients.js';
+import { getConfig, validateConfig } from './src/config/env.js';
+import { createSearchService } from './src/services/searchService.js';
+import { renderHTML } from './src/utils/htmlConsoleRenderer.js';
+
+// Load environment variables from .env file
+dotenv.config();
+
+function printUsage() {
+  console.log('Usage: node searchCLI.js <question>');
+  console.log('');
+  console.log('Example:');
+  console.log('  node searchCLI.js "What are the latest developments in AI?"');
+}
+
+function createSimpleBroadcast() {
+  return (message, type = 'info', data = null) => {
+    const timestamp = new Date().toLocaleTimeString();
+    const prefix = type === 'error' ? '❌' : type === 'warning' ? '⚠️' : type === 'success' ? '✅' : 'ℹ️';
+    console.log(`[${timestamp}] ${prefix} ${message}`);
+  };
+}
+
+async function runCLI() {
+  const args = process.argv.slice(2);
+  
+  if (args.length === 0 || args.includes('--help') || args.includes('-h')) {
+    printUsage();
+    process.exit(args.includes('--help') || args.includes('-h') ? 0 : 1);
+  }
+
+  const question = args.join(' ');
+
+  try {
+    const config = getConfig();
+    validateConfig(config);
+
+    const broadcast = createSimpleBroadcast();
+    const clients = createClients(config);
+    const searchService = createSearchService({
+      ...clients,
+      broadcast,
+    });
+
+    broadcast(`Starting search for: "${question}"`, 'info');
+
+    const result = await searchService.search(question);
+
+    console.log('');
+    console.log('═══════════════════════════════════════════════════════════');
+    console.log('FINAL ANSWER:');
+    console.log('═══════════════════════════════════════════════════════════');
+    console.log(renderHTML(result.fullAnswerHTMLSnippet) || 'No answer generated');
+    console.log('');
+    
+    if (result.mostRelevantSources && result.mostRelevantSources.length > 0) {
+      console.log('SOURCES:');
+      result.mostRelevantSources.forEach((source, index) => {
+        console.log(`  ${index + 1}. ${source}`);
+      });
+    }
+    console.log('═══════════════════════════════════════════════════════════');
+
+    process.exit(0);
+  } catch (error) {
+    console.error('');
+    console.error('❌ Error:', error.message);
+    if (error.details) {
+      console.error('   Details:', error.details);
+    }
+    process.exit(1);
+  }
+}
+
+runCLI();
--- a/src/config/env.js
+++ b/src/config/env.js
@@ -10,6 +10,7 @@ export function getConfig() {
    host: process.env.HOST || '0.0.0.0',
    exaApiKey: process.env.EXA_API_KEY,
    openRouterApiKey: process.env.OPENROUTER_API_KEY,
+    maintenanceMode: process.env.MAINTENANCE_MODE === 'true',
  };
 }

--- a/src/maintenanceApp.js
+++ b/src/maintenanceApp.js
@@ -0,0 +1,55 @@
+import express from 'express';
+
+export function createMaintenanceApp() {
+  const app = express();
+
+  app.get('/{*path}', (req, res) => {
+    res.status(503).send(`
+      <!DOCTYPE html>
+      <html lang="en">
+      <head>
+        <meta charset="UTF-8">
+        <meta name="viewport" content="width=device-width, initial-scale=1.0">
+        <title>Under Construction</title>
+        <style>
+          body {
+            font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, sans-serif;
+            display: flex;
+            justify-content: center;
+            align-items: center;
+            height: 100vh;
+            margin: 0;
+            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+            color: white;
+          }
+          .container {
+            text-align: center;
+            padding: 2rem;
+          }
+          h1 {
+            font-size: 3rem;
+            margin-bottom: 1rem;
+          }
+          p {
+            font-size: 1.2rem;
+            opacity: 0.9;
+          }
+          .icon {
+            font-size: 4rem;
+            margin-bottom: 1rem;
+          }
+        </style>
+      </head>
+      <body>
+        <div class="container">
+          <div class="icon">🚧</div>
+          <h1>Under Construction</h1>
+          <p>Please return later.</p>
+        </div>
+      </body>
+      </html>
+    `);
+  });
+
+  return app;
+}
--- a/src/mcpServer.js
+++ b/src/mcpServer.js
@@ -0,0 +1,124 @@
+import { Server } from '@modelcontextprotocol/sdk/server/index.js';
+import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js';
+import {
+  CallToolRequestSchema,
+  ListToolsRequestSchema,
+} from '@modelcontextprotocol/sdk/types.js';
+import { createClients } from './clients.js';
+import { getConfig, validateConfig } from './config/env.js';
+import { createSearchService } from './services/searchService.js';
+
+function createSimpleBroadcast() {
+  return (message, type = 'info', data = null) => {
+    // Log to stderr so it doesn't interfere with MCP protocol on stdout
+    const timestamp = new Date().toLocaleTimeString();
+    const prefix = type === 'error' ? '❌' : type === 'warning' ? '⚠️' : type === 'success' ? '✅' : 'ℹ️';
+    console.error(`[${timestamp}] ${prefix} ${message}`);
+  };
+}
+
+export async function startMCPServer() {
+  const config = getConfig();
+  validateConfig(config);
+
+  const clients = createClients(config);
+  const broadcast = createSimpleBroadcast();
+  const searchService = createSearchService({
+    ...clients,
+    broadcast,
+  });
+
+  const server = new Server(
+    {
+      name: 'search-agent',
+      version: '1.0.0',
+    },
+    {
+      capabilities: {
+        tools: {},
+      },
+    },
+  );
+
+  // Handler for listing available tools
+  server.setRequestHandler(ListToolsRequestSchema, async () => {
+    return {
+      tools: [
+        {
+          name: 'search',
+          description: 'Deep Web Research',
+          inputSchema: {
+            type: 'object',
+            properties: {
+              question: {
+                type: 'string',
+                description: 'The question or topic to search for',
+              },
+              previousClarification: {
+                type: 'string',
+                description: 'Optional: Previous clarification from the user if the question needed refinement',
+              },
+              originalQuestion: {
+                type: 'string',
+                description: 'Optional: The original question if this is a follow-up',
+              },
+            },
+            required: ['question'],
+          },
+        },
+      ],
+    };
+  });
+
+  // Handler for calling tools
+  server.setRequestHandler(CallToolRequestSchema, async (request) => {
+    const { name, arguments: args } = request.params;
+
+    if (name !== 'search') {
+      throw new Error(`Unknown tool: ${name}`);
+    }
+
+    const { question, previousClarification, originalQuestion } = args;
+
+    if (!question) {
+      throw new Error('Missing required parameter: question');
+    }
+
+    try {
+      broadcast(`MCP: Starting search for: "${question}"`, 'info');
+
+      const result = await searchService.search(question, previousClarification, originalQuestion);
+
+      broadcast('MCP: Search completed successfully', 'success');
+
+      // Return the result in a structured format
+      return {
+        content: [
+          {
+            type: 'text',
+            text: result.fullAnswerHTMLSnippet || 'No answer generated',
+          },
+        ],
+        isError: false,
+      };
+    } catch (error) {
+      broadcast(`MCP: Error: ${error.message}`, 'error');
+      
+      return {
+        content: [
+          {
+            type: 'text',
+            text: `Error: ${error.message}`,
+          },
+        ],
+        isError: true,
+      };
+    }
+  });
+
+  // Start the server with stdio transport
+  const transport = new StdioServerTransport();
+  await server.connect(transport);
+
+  console.error('🔌 MCP Search Agent server running on stdio');
+}
--- a/src/routes/search.js
+++ b/src/routes/search.js
@@ -5,7 +5,7 @@ export function createSearchRouter(searchService, broadcast) {
  const router = Router();

  router.post('/', async (request, response) => {
-    const { question } = request.body;
+    const { question, previousClarification, originalQuestion } = request.body;

    if (!question) {
      response.status(400).json({
@@ -16,7 +16,7 @@ export function createSearchRouter(searchService, broadcast) {
    }

    try {
-      const result = await searchService.search(question);
+      const result = await searchService.search(question, previousClarification, originalQuestion);
      response.json(result);
    } catch (error) {
      if (error instanceof SearchServiceError) {
--- a/src/server.js
+++ b/src/server.js
@@ -1,37 +1,50 @@
 import { createApp } from './app.js';
+import { createMaintenanceApp } from './maintenanceApp.js';
 import { createClients } from './clients.js';
 import { getConfig, validateConfig } from './config/env.js';
 import { createSseHub } from './lib/sseHub.js';
 import { createSearchService } from './services/searchService.js';

-function logStartup(host, port) {
-  console.log(`REST Search Service running at http://${host}:${port}`);
-  console.log(`Web UI: http://localhost:${port}`);
-  console.log('API Documentation:');
-  console.log('   POST /search - Search for a query and return summarized results');
-  console.log('   GET  /health - Health check endpoint');
-  console.log('   GET  /stream - SSE endpoint for streaming log messages');
-  console.log('\nExample:');
-  console.log(`   curl -X POST http://${host}:${port}/search \\`);
-  console.log('     -H "Content-Type: application/json" \\');
-  console.log('     -d \'{"question": "What are the latest developments in AI?"}\'');
-  console.log('\nSSE Log Stream:');
-  console.log(`   Open http://localhost:${port}/stream in a browser or use EventSource in JavaScript`);
+function logStartup(host, port, isMaintenance) {
+  if (isMaintenance) {
+    console.log(`🚧 Maintenance Mode running at http://${host}:${port}`);
+    console.log('All requests will receive "Under Construction" page');
+  } else {
+    console.log(`REST Search Service running at http://${host}:${port}`);
+    console.log(`Web UI: http://localhost:${port}`);
+    console.log('API Documentation:');
+    console.log('   POST /search - Search for a query and return summarized results');
+    console.log('   GET  /health - Health check endpoint');
+    console.log('   GET  /stream - SSE endpoint for streaming log messages');
+    console.log('\nExample:');
+    console.log(`   curl -X POST http://${host}:${port}/search \\`);
+    console.log('     -H "Content-Type: application/json" \\');
+    console.log('     -d \'{"question": "What are the latest developments in AI?"}\'');
+    console.log('\nSSE Log Stream:');
+    console.log(`   Open http://localhost:${port}/stream in a browser or use EventSource in JavaScript`);
+  }
 }

 export function startServer() {
  const config = getConfig();
  validateConfig(config);

-  const clients = createClients(config);
-  const sseHub = createSseHub();
-  const searchService = createSearchService({
-    ...clients,
-    broadcast: sseHub.broadcast,
-  });
-  const app = createApp({ searchService, sseHub });
+  const isMaintenance = config.maintenanceMode;
+
+  let app;
+  if (isMaintenance) {
+    app = createMaintenanceApp();
+  } else {
+    const clients = createClients(config);
+    const sseHub = createSseHub();
+    const searchService = createSearchService({
+      ...clients,
+      broadcast: sseHub.broadcast,
+    });
+    app = createApp({ searchService, sseHub });
+  }

  app.listen(config.port, config.host, () => {
-    logStartup(config.host, config.port);
+    logStartup(config.host, config.port, isMaintenance);
  });
 }
--- a/src/services/extractionLogger.js
+++ b/src/services/extractionLogger.js
@@ -0,0 +1,74 @@
+import fs from 'fs/promises';
+import path from 'path';
+import { fileURLToPath } from 'url';
+
+const __filename = fileURLToPath(import.meta.url);
+const __dirname = path.dirname(__filename);
+
+const LOG_DIR = path.join(__dirname, '../../logs');
+const LOG_FILE = path.join(LOG_DIR, 'extraction.log');
+
+/**
+ * Ensures the log directory exists
+ */
+async function ensureLogDirectory() {
+  try {
+    await fs.mkdir(LOG_DIR, { recursive: true });
+  } catch (error) {
+    console.error('Failed to create log directory:', error);
+    throw error;
+  }
+}
+
+/**
+ * Formats a timestamp for logging
+ */
+function formatTimestamp() {
+  return new Date().toISOString();
+}
+
+/**
+ * Logs an extraction event with input and output
+ * @param {Object} input - The input data (search result from Exa)
+ * @param {string} output - The extracted text content
+ */
+export async function logExtraction(input, output) {
+  try {
+    await ensureLogDirectory();
+
+    const timestamp = formatTimestamp();
+    const logEntry = {
+      timestamp,
+      input: {
+        resultCount: input?.results?.length || 0,
+        results: input?.results?.map((r) => ({
+          title: r.title,
+          url: r.url,
+          textPreview: r.text?.substring(0, 200) + (r.text?.length > 200 ? '...' : ''),
+          summaryPreview: r.summary?.substring(0, 200) + (r.summary?.length > 200 ? '...' : ''),
+          highlightsCount: r.highlights?.length || 0,
+          publishedDate: r.publishedDate,
+          author: r.author,
+        })),
+      },
+      output: {
+        length: output.length,
+        preview: output.substring(0, 500) + (output.length > 500 ? '...' : ''),
+      },
+    };
+
+    const logLine = `${timestamp} | Input: ${JSON.stringify(logEntry.input)} | Output: [${logEntry.output.length} chars] ${logEntry.output.preview}\n`;
+
+    await fs.appendFile(LOG_FILE, logLine, 'utf8');
+  } catch (error) {
+    console.error('Failed to log extraction:', error);
+    // Don't throw - logging should not break the main functionality
+  }
+}
+
+/**
+ * Gets the path to the extraction log file
+ */
+export function getLogFilePath() {
+  return LOG_FILE;
+}
--- a/src/services/openRouterLogger.js
+++ b/src/services/openRouterLogger.js
@@ -0,0 +1,58 @@
+import fs from 'fs/promises';
+import path from 'path';
+import { fileURLToPath } from 'url';
+
+const __filename = fileURLToPath(import.meta.url);
+const __dirname = path.dirname(__filename);
+
+const LOG_DIR = path.join(__dirname, '../../logs');
+
+/**
+ * Ensures the log directory exists
+ */
+async function ensureLogDirectory() {
+  try {
+    await fs.mkdir(LOG_DIR, { recursive: true });
+  } catch (error) {
+    console.error('Failed to create log directory:', error);
+    throw error;
+  }
+}
+
+/**
+ * Formats a timestamp for logging
+ */
+function formatTimestamp() {
+  return new Date().toISOString();
+}
+
+/**
+ * Logs an OpenRouter API call with params and response
+ * @param {string} operation - The operation name (e.g., 'summarizeSources', 'summarizeFinalAnswer')
+ * @param {Object} params - The request parameters sent to OpenRouter
+ * @param {Object} response - The response from OpenRouter
+ * @param {Error} [error] - Optional error if the call failed
+ */
+export async function logOpenRouterCall(operation, text, params, response, error = null) {
+  try {
+    await ensureLogDirectory();
+
+    const timestamp = formatTimestamp();
+    const logFileName = `openrouter-${timestamp.replace(/[:.]/g, '-')}.log`;
+    const logFilePath = path.join(LOG_DIR, logFileName);
+
+    const logContent = `${timestamp} | ${operation}\n\nParams:\n${JSON.stringify(params, null, 2)}\n\nResponse:\n${JSON.stringify(response, null, 2)}${error ? `\n\nError: ${error.message}` : ''}\n`;
+
+    await fs.writeFile(logFilePath, text + logContent, 'utf8');
+  } catch (logError) {
+    console.error('Failed to log OpenRouter call:', logError);
+    // Don't throw - logging should not break the main functionality
+  }
+}
+
+/**
+ * Gets the path to the OpenRouter log directory
+ */
+export function getOpenRouterLogDirPath() {
+  return LOG_DIR;
+}
--- a/src/services/openRouterService.js
+++ b/src/services/openRouterService.js
@@ -1,5 +1,14 @@
+import { logOpenRouterCall } from './openRouterLogger.js';
+
 function parseResponse(response) {
-  return JSON.parse(response.choices[0].message.content);
+  if(!response?.usage?.cost) console.log(response);
+  console.log('OpenRouter API call cost:', response?.usage);
+  return { 
+    cost: response?.usage?.cost,
+    prompt_tokens: response?.usage?.prompt_tokens,
+    completion_tokens: response?.usage?.completion_tokens,
+    data: JSON.parse(response.choices[0].message.content) 
+  };
 }

 export async function summarizeSources({ openrouter, text, question }) {
@@ -16,9 +25,9 @@ export async function summarizeSources({ openrouter, text, question }) {
      { role: 'user', content: text },
    ],
    reasoning: { effort: 'low' },
-    responseFormat: {
+    response_format: {
      type: 'json_schema',
-      jsonSchema: {
+      json_schema: {
        name: 'search_summaries',
        strict: true,
        schema: {
@@ -45,39 +54,47 @@ export async function summarizeSources({ openrouter, text, question }) {
    stream: false,
  };

-  const response = await openrouter.chat.send({ chatRequest: params });
+  // Using direct fetch API instead of OpenRouter SDK
+  const apiKey = process.env.OPENROUTER_API_KEY;
+  const fetchResponse = await fetch('https://openrouter.ai/api/v1/chat/completions', {
+    method: 'POST',
+    headers: {
+      Authorization: `Bearer ${apiKey}`,
+      'Content-Type': 'application/json',
+    },
+    body: JSON.stringify(params),
+  });
+  const response = await fetchResponse.json();
+  await logOpenRouterCall('summarizeSources', text, params, response);
  return parseResponse(response);
 }

-export async function summarizeFinalAnswer({ openrouter, text, question }) {
+export async function summarizeDetail({ text, url, question }) {
  const prompt = `
-    You are a search result analyst. Today is the date of ${new Date().toLocaleDateString()}.
-    Based on the following search results for the query "${question}",
-    Summarize the search results to answer the original query. Use Emoji and HTML. Tags allowed: <b>, <i>, <u>, <ul>, <li>, <span style="color:...">, <p> <div> <hr/>
-    Also provide the most relevant sources.
+    You are a search result analyst.
+    The original query was "${question}".
+    A detailed search on the following source "${url}" has returned a result,
+    filter this result to extract the most relevant information to answer the original query.
  `;

  const params = {
-    model: 'openai/gpt-5.4-mini',
+    model: 'openai/gpt-oss-120b:nitro',
    messages: [
      { role: 'system', content: prompt },
      { role: 'user', content: text },
    ],
-    reasoning: { effort: 'none' },
-    responseFormat: {
+    reasoning: { effort: 'low' },
+    response_format: {
      type: 'json_schema',
-      jsonSchema: {
-        name: 'response',
+      json_schema: {
+        name: 'summary',
        strict: true,
        schema: {
          type: 'object',
-          required: ['fullAnswerHTMLSnippet', 'mostRelevantSources'],
+          required: ['summary'],
+          additionalProperties: false,
          properties: {
-            fullAnswerHTMLSnippet: { type: 'string' },
-            mostRelevantSources: {
-              type: 'array',
-              items: { type: 'string' },
-            },
+            summary: { type: 'string', description: 'Filtered summary of the relevant information' },
          },
        },
      },
@@ -85,6 +102,226 @@ export async function summarizeFinalAnswer({ openrouter, text, question }) {
    stream: false,
  };

-  const response = await openrouter.chat.send({ chatRequest: params });
+  // Using direct fetch API instead of OpenRouter SDK
+  const apiKey = process.env.OPENROUTER_API_KEY;
+  const fetchResponse = await fetch('https://openrouter.ai/api/v1/chat/completions', {
+    method: 'POST',
+    headers: {
+      Authorization: `Bearer ${apiKey}`,
+      'Content-Type': 'application/json',
+    },
+    body: JSON.stringify(params),
+  });
+  const response = await fetchResponse.json();
+  await logOpenRouterCall('summarizeDetail', text, params, response);
  return parseResponse(response);
 }
+
+export async function rephraseQuestion({ question, previousClarification, originalQuestion }) {
+
+  if(previousClarification) {
+    const prompt = `
+      You are a search query expert. You are given a question and you return
+      a search query for a web search engine that would return the best results to answer the question. 
+      Do NOT restrict the query using site: operator.
+      Also give a list of 2 supplementary search queries to deepen the search. 
+      Today is the date of ${new Date().toLocaleDateString()}. 
+      The user has provided this clarification "${previousClarification}" to the original question: ` + originalQuestion;
+
+    const params = {
+      model: 'z-ai/glm-4.7:nitro',
+      messages: [
+        { role: 'system', content: prompt },
+        { role: 'user', content: question },
+      ],
+      reasoning: { effort: 'none' },
+      stream: false,
+      response_format: {
+        type: 'json_schema', json_schema: { 
+          name: 'queries', strict: true, schema: {
+            required: [ 'query', 'supplementaryQueries'], type: 'object', additionalProperties: false, properties: {
+              query: { type: 'string' },
+              supplementaryQueries: { type: 'array', items: { type: 'string' } },
+      } } } } 
+    };
+
+    const apiKey = process.env.OPENROUTER_API_KEY;
+    const fetchResponse = await fetch('https://openrouter.ai/api/v1/chat/completions', {
+      method: 'POST',
+      headers: {
+        Authorization: `Bearer ${apiKey}`,
+        'Content-Type': 'application/json',
+      },
+      body: JSON.stringify(params),
+    });
+    const response = await fetchResponse.json();
+    await logOpenRouterCall('rephraseQuestion', question,params, response);
+    return parseResponse(response);
+  }
+
+
+  const prompt = `
+    You are a search query expert. You are given a question and you return
+    a search query for a web search engine that would return the best results to answer the question. 
+    Do NOT restrict the query using site: operator.
+    Also give a list of 2 supplementary search queries to deepen the search. 
+    Today is the date of ${new Date().toLocaleDateString()}. 
+    The user cannot ask questions that a web search engine cannot answer. 
+    Like "Who are you". 
+    If the question is ambiguous or unsuited for a web search, you can ask for clarification.
+    ${previousClarification ? `The user has provided this clarification to the original question: "${previousClarification}". Use this clarification to refine the search query.` : ''}
+  `;
+
+  const params = {
+    model: 'z-ai/glm-4.7:nitro',
+    messages: [
+      { role: 'system', content: prompt },
+      { role: 'user', content: question },
+    ],
+    reasoning: { effort: 'none' },
+    stream: false,
+    response_format: {
+      type: 'json_schema', json_schema: { 
+        name: 'queries', strict: true, schema: {
+          required: ['needsClarification', 'clarification', 'query', 'supplementaryQueries'], type: 'object', additionalProperties: false, properties: {
+            needsClarification: { type: 'boolean', description: 'Indicates if the question is ambiguous and needs clarification' },
+            clarification: { type: 'string', description: 'If needsClarification is true, this field contains the clarification question to ask the user. Otherwise, it is an empty string.' },
+            query: { type: 'string' },
+            supplementaryQueries: { type: 'array', items: { type: 'string' } },
+    } } } } 
+  };
+
+  const apiKey = process.env.OPENROUTER_API_KEY;
+  const fetchResponse = await fetch('https://openrouter.ai/api/v1/chat/completions', {
+    method: 'POST',
+    headers: {
+      Authorization: `Bearer ${apiKey}`,
+      'Content-Type': 'application/json',
+    },
+    body: JSON.stringify(params),
+  });
+  const response = await fetchResponse.json();
+  await logOpenRouterCall('rephraseQuestion', question,params, response);
+  return parseResponse(response);
+}
+
+export async function summarizeFinalAnswer({ openrouter, text, question }) {
+  const apiKey = process.env.OPENROUTER_API_KEY;
+  
+  // Step 1: Get summary, sources, and suggested searches
+  const summaryPrompt = `
+    You are a search result analyst. Today is the date of ${new Date().toLocaleDateString()}.
+    Based on the following search results for the query "${question}",
+    Summarize the search results to answer the original query in a detailed manner. 
+    Also provide the most relevant sources. Answer in the language of the question. You may suggest 2 followup searches to the user.
+  `;
+
+  const summaryParams = {
+    model: 'openai/gpt-oss-120b:nitro',
+    messages: [
+      { role: 'system', content: summaryPrompt },
+      { role: 'user', content: text },
+    ],
+    reasoning: { effort: 'low' },
+    response_format: {
+      type: 'json_schema',
+      json_schema: {
+        name: 'summary',
+        strict: true,
+        schema: {
+          type: 'object',
+          required: ['summary', 'mostRelevantSources', 'suggestedSearches'],
+          properties: {
+            summary: { type: 'string' },
+            mostRelevantSources: { type: 'array', items: { type: 'string' } },
+            suggestedSearches: { type: 'array', items: { type: 'string' } },
+          },
+        },
+      },
+    },
+    stream: false,
+  };
+
+  const summaryFetchResponse = await fetch('https://openrouter.ai/api/v1/chat/completions', {
+    method: 'POST',
+    headers: {
+      Authorization: `Bearer ${apiKey}`,
+      'Content-Type': 'application/json',
+    },
+    body: JSON.stringify(summaryParams),
+  });
+  const summaryResponse = await summaryFetchResponse.json();
+  await logOpenRouterCall('summarizeFinalAnswer-step1', text, summaryParams, summaryResponse);
+  const summaryData = parseResponse(summaryResponse);
+  
+  // Step 2: Enrich the summary with HTML tags and emojis
+  const enrichmentPrompt = `
+    You are a content formatter. Take the following summary and enrich it with emojis and HTML tags.
+    Allowed tags: <b>, <i>, <u>, <pre>, <ul>, <li>, <span style="color:...">, <p>, <div>, <hr/>
+    Make it visually appealing and easy to read.
+  `;
+
+  const enrichmentParams = {
+    model: 'qwen/qwen3-235b-a22b-2507:nitro',
+    messages: [
+      { role: 'system', content: enrichmentPrompt },
+      { role: 'user', content: summaryData.data.summary },
+    ],
+    reasoning: { effort: 'low' },
+    response_format: {
+      type: 'json_schema',
+      json_schema: {
+        name: 'enrichedSummary',
+        strict: true,
+        schema: {
+          type: 'object',
+          required: ['fullAnswerHTMLSnippet'],
+          properties: {
+            fullAnswerHTMLSnippet: { type: 'string' },
+          },
+        },
+      },
+    },
+    stream: false,
+  };
+
+  const enrichmentFetchResponse = await fetch('https://openrouter.ai/api/v1/chat/completions', {
+    method: 'POST',
+    headers: {
+      Authorization: `Bearer ${apiKey}`,
+      'Content-Type': 'application/json',
+    },
+    body: JSON.stringify(enrichmentParams),
+  });
+  const enrichmentResponse = await enrichmentFetchResponse.json();
+  await logOpenRouterCall('summarizeFinalAnswer-step2', summaryData.data.summary, enrichmentParams, enrichmentResponse);
+  const enrichmentData = parseResponse(enrichmentResponse);
+  
+  // Combine results with separate cost breakdowns
+  return {
+    totalCost: summaryData.cost + enrichmentData.cost,
+    totalPromptTokens: summaryData.prompt_tokens + enrichmentData.prompt_tokens,
+    totalCompletionTokens: summaryData.completion_tokens + enrichmentData.completion_tokens,
+    steps: [
+      {
+        name: 'summary',
+        model: 'openai/gpt-oss-120b:nitro',
+        cost: summaryData.cost,
+        promptTokens: summaryData.prompt_tokens,
+        completionTokens: summaryData.completion_tokens,
+      },
+      {
+        name: 'enrichment',
+        model: 'qwen/qwen3-235b-a22b-2507:nitro',
+        cost: enrichmentData.cost,
+        promptTokens: enrichmentData.prompt_tokens,
+        completionTokens: enrichmentData.completion_tokens,
+      },
+    ],
+    data: {
+      fullAnswerHTMLSnippet: enrichmentData.data.fullAnswerHTMLSnippet,
+      mostRelevantSources: summaryData.data.mostRelevantSources,
+      suggestedSearches: summaryData.data.suggestedSearches,
+    },
+  };
+}
--- a/src/services/searchFormatter.js
+++ b/src/services/searchFormatter.js
@@ -19,7 +19,7 @@ function wrapText(text, maxLineLength = 68) {
  return output;
 }

-export function formatSummarySources(sources) {
+export function formatSummarySources(sources,supplementaryResults=[]) {
  let output = `\n${'='.repeat(70)}\n`;
  output += ` ${'SUMMARY'.padStart(35).padEnd(69)}\n`;
  output += `${'='.repeat(70)}\n`;
@@ -38,6 +38,13 @@ export function formatSummarySources(sources) {
    }
  });

+  if (supplementaryResults.length > 0) {
+    supplementaryResults.forEach((result) => {
+      output += `\n${'-'.repeat(70)}\n`;
+      output += JSON.stringify(result, null, 2);
+    });
+  }
+
  output += `\n${'='.repeat(70)}\n`;
  output += `Total sources: ${sources.length}\n`;
  output += `${'='.repeat(70)}\n`;
--- a/src/services/searchService.js
+++ b/src/services/searchService.js
@@ -1,6 +1,16 @@
 import { extractContent } from './extractContent.js';
-import { summarizeFinalAnswer, summarizeSources } from './openRouterService.js';
+import { logExtraction } from './extractionLogger.js';
+import { summarizeFinalAnswer, summarizeSources, summarizeDetail, rephraseQuestion } from './openRouterService.js';
 import { formatSummarySources } from './searchFormatter.js';
+import { get_encoding } from 'tiktoken';
+
+const encoding = get_encoding('cl100k_base');
+
+function countTokens(text) {
+  if (!text) return 0;
+  const tokens = encoding.encode(text);
+  return tokens.length;
+}

 const EXA_SEARCH_OPTIONS = {
  numResults: 10,
@@ -47,7 +57,23 @@ async function fetchDetailedContents({ exa, question, sources, broadcast }) {
        );

        const content = await exa.getContents([source.url], EXA_CONTENT_OPTIONS(question));
-        return { url: source.url, content };
+
+        console.log(content.results[0].highlights);
+        return { url: source.url, content , cost: content.costDollars.total };
+
+        /*const summary = await summarizeDetail({text: content.results, url: source.url, question})
+
+        const cost2 = {
+          type:'openrouter_detail_summary', 
+          amount: summary.cost,
+          prompt_tokens: summary.prompt_tokens,
+          completion_tokens: summary.completion_tokens,
+          model: 'openai/gpt-oss-120b:nitro'
+        };
+
+        const summaryIsLonger = JSON.stringify(summary.data).length > JSON.stringify(content.results).length;
+
+        return { url: source.url, content: summaryIsLonger ? content.results : source.summary, cost: content.costDollars.total, cost2 };*/
      } catch (error) {
        broadcast(`⚠️ Could not fetch content for ${source.url}: ${error.message}`, 'warning');
        return { url: source.url, content: null };
@@ -71,19 +97,123 @@ function enrichSourcesWithDetails(sources, detailedContents) {
  }
 }

+// Helper function to build cost breakdown
+function buildCostBreakdown(cost) {
+  // Print cost breakdown as a formatted table
+  console.log('\n=== Cost Breakdown ===');
+  console.table(
+    cost.map((item, index) => ({
+      '#': index + 1,
+      Type: item.type,
+      Model: item.model || '-',
+      'Cost (USD)': `$${item.amount.toFixed(6)}`,
+    })),
+  );
+  const totalCost = cost.reduce((sum, item) => sum + item.amount, 0);
+  console.log(`Total: $${totalCost.toFixed(6)}\n`);
+
+  // Build cost breakdown table for API response
+  const costBreakdown = cost.map((item, index) => ({
+    index: index + 1,
+    type: item.type,
+    model: item.model || '-',
+    prompt_tokens: item.prompt_tokens,
+    completion_tokens: item.completion_tokens,
+    cost: `$${item.amount.toFixed(6)}`,
+  }));
+
+  // Add total to the breakdown
+  costBreakdown.push({
+    index: costBreakdown.length + 1,
+    type: 'Total',
+    cost: `$${totalCost.toFixed(6)}`,
+  });
+
+  return costBreakdown;
+}
+
 export function createSearchService({ exa, openrouter, broadcast }) {
  return {
-    async search(question) {
-      broadcast(`🔍 Search request: "${question}"`, 'info', { question });
+    async search(question, previousClarification, originalQuestion) {
+      let finalSummary;
+      const cost=[];
+      let rephrasedQuestion;

-      broadcast('Searching with Exa...', 'info');
-      const result = await exa.search(question, EXA_SEARCH_OPTIONS);
+      try {
+        const rephraseResult = await rephraseQuestion({question, previousClarification, originalQuestion});
+        rephrasedQuestion = rephraseResult.data;
+        cost.push({
+          type:'openrouter_rephrase', 
+          amount: rephraseResult.cost,
+          prompt_tokens: rephraseResult.prompt_tokens,
+          completion_tokens: rephraseResult.completion_tokens,
+          model: 'z-ai/glm-4.7:nitro'
+        });
+      } catch (error) {
+        throw new SearchServiceError('Failed to generate summary', 500, error);
+      }
+      if (rephrasedQuestion.needsClarification) {
+        finalSummary = {
+          fullAnswerHTMLSnippet: rephrasedQuestion.clarification,
+          clarificationNeeded: true,
+          originalQuestion: question,
+          mostRelevantSources: [],
+        };
+        // Attach cost breakdown to the final summary
+        finalSummary.costBreakdown = buildCostBreakdown(cost);
+
+        return finalSummary;
+       
+      }
+
+      // Limit to first 2 supplementary queries
+      const limitedQueries = rephrasedQuestion.supplementaryQueries.slice(0, 2);
+      //limitedQueries.push(rephrasedQuestion.query);
+      const supplementaryResults = [];
+      for (const item of limitedQueries) {
+        console.log('Supplementary Query:', item);
+        const result = await exa.search(item, {
+          numResults: 2,
+          type: 'auto',
+          contents: {
+            highlights: {
+              maxCharacters: 2000,
+            },
+          },
+        });
+        supplementaryResults.push({
+          query: item,
+          highlights: result.results.map(r => r.highlights),
+        });
+        const outputTokens = countTokens(JSON.stringify(result.results));
+        cost.push({ 
+          type: 'exa_search_complement', 
+          amount: result.costDollars.total,
+          prompt_tokens: 0,
+          completion_tokens: outputTokens
+        });
+      }
+
+
+      broadcast('Searching with Exa for '+rephrasedQuestion.query, 'info');
+      const result = await exa.search(rephrasedQuestion.query, EXA_SEARCH_OPTIONS);
      broadcast(`✅ Found ${result.results.length} results`, 'success', {
        count: result.results.length,
      });
+      
+      const outputTokens = countTokens(JSON.stringify(result.results));
+      cost.push({
+        type:'exa_search', 
+        amount: result.costDollars.total,
+        prompt_tokens: 0,
+        completion_tokens: outputTokens
+      });

      const extractedContent = extractContent(result);

+      // Log the extraction
+      await logExtraction(result, extractedContent);
+
      if (!extractedContent.trim()) {
        throw new SearchServiceError('No content extracted from results');
      }
@@ -91,18 +221,27 @@ export function createSearchService({ exa, openrouter, broadcast }) {
      broadcast('📝 Generating summary with OpenRouter...', 'info');

      let summary;
+      
      try {
-        summary = await summarizeSources({
+        const summaryResult = await summarizeSources({
          openrouter,
          text: extractedContent,
          question,
        });
+        summary = summaryResult.data;
+        cost.push({
+          type:'openrouter_rank', 
+          amount: summaryResult.cost,
+          prompt_tokens: summaryResult.prompt_tokens,
+          completion_tokens: summaryResult.completion_tokens,
+          model: 'openai/gpt-oss-120b:nitro'
+        });
      } catch (error) {
        throw new SearchServiceError('Failed to generate summary', 500, error);
      }

      if (!summary?.sources) {
-        throw new SearchServiceError('Failed to generate summary');
+        throw new SearchServiceError('Failed to generate summary for query: ' + question + '. No sources returned:'+ JSON.stringify(summary, null, 2));
      }

      broadcast(`✅ Generated summaries for ${summary.sources.length} sources`, 'success', {
@@ -117,18 +256,54 @@ export function createSearchService({ exa, openrouter, broadcast }) {
        broadcast,
      });

-      broadcast('🔧 Enhancing summaries with detailed content...', 'info');
      enrichSourcesWithDetails(summary.sources, detailedContents);
+      for (const detailed of detailedContents) {
+        if (detailed.cost) {
+          const outputTokens = countTokens(JSON.stringify(detailed.content));
+          cost.push({
+            type:'exa_get_content', 
+            amount: detailed.cost,
+            prompt_tokens: 0,
+            completion_tokens: outputTokens
+          });
+        }
+        //if (detailed.cost2) {
+        //  cost.push(detailed.cost2);
+        //}
+      }

      broadcast('📊 Generating final summary...', 'info');

-      let finalSummary;
+      
      try {
-        finalSummary = await summarizeFinalAnswer({
+        const finalSummaryResult = await summarizeFinalAnswer({
          openrouter,
-          text: formatSummarySources(summary.sources),
+          text: formatSummarySources(summary.sources,supplementaryResults),
          question,
        });
+        finalSummary = finalSummaryResult.data;
+        
+        // Push each step separately for detailed cost tracking
+        if (finalSummaryResult.steps && Array.isArray(finalSummaryResult.steps)) {
+          for (const step of finalSummaryResult.steps) {
+            cost.push({
+              type: `openrouter_${step.name}`,
+              amount: step.cost,
+              prompt_tokens: step.promptTokens,
+              completion_tokens: step.completionTokens,
+              model: step.model,
+            });
+          }
+        } else {
+          // Fallback for backward compatibility
+          cost.push({
+            type: 'openrouter_final_summary',
+            amount: finalSummaryResult.totalCost,
+            prompt_tokens: finalSummaryResult.totalPromptTokens,
+            completion_tokens: finalSummaryResult.totalCompletionTokens,
+            model: 'openai/gpt-oss-120b:nitro',
+          });
+        }
      } catch (error) {
        throw new SearchServiceError('Failed to generate final summary', 500, error);
      }
@@ -142,6 +317,9 @@ export function createSearchService({ exa, openrouter, broadcast }) {
        sourcesCount: finalSummary.mostRelevantSources?.length || 0,
      });

+      // Attach cost breakdown to the final summary
+      finalSummary.costBreakdown = buildCostBreakdown(cost);
+
      return finalSummary;
    },
  };
--- a/src/utils/htmlConsoleRenderer.js
+++ b/src/utils/htmlConsoleRenderer.js
@@ -0,0 +1,88 @@
+import chalk from 'chalk';
+
+/**
+ * Simple HTML to console renderer using chalk for styling.
+ * Supports: <b>, <i>, <u>, <ul>, <li>, <span style="color:...">, <p>, <div>, <hr/>
+ */
+
+// Color mapping for span styles
+const colorMap = {
+  red: chalk.red,
+  blue: chalk.blue,
+  green: chalk.green,
+  yellow: chalk.yellow,
+  cyan: chalk.cyan,
+  magenta: chalk.magenta,
+  white: chalk.white,
+  gray: chalk.gray,
+  grey: chalk.gray,
+  black: chalk.black,
+};
+
+/**
+ * Parse HTML string and convert to styled console output
+ * @param {string} html - HTML string to render
+ * @returns {string} - Formatted string with chalk styling
+ */
+export function renderHTML(html) {
+  if (!html) return '';
+
+  let text = html;
+
+  // Handle <hr/> as a line
+  text = text.replace(/<hr\s*\/?>/gi, '\n' + '─'.repeat(60) + '\n');
+
+  // Handle <span style="color:...">content</span>
+  text = text.replace(/<span\s+style\s*=\s*["']color:\s*(\w+)["']\s*>([\s\S]*?)<\/span>/gi, (match, color, content) => {
+    const colorFn = colorMap[color.toLowerCase()];
+    return colorFn ? colorFn(content) : content;
+  });
+
+  // Handle <b>content</b> - bold
+  text = text.replace(/<b>([\s\S]*?)<\/b>/gi, (match, content) => chalk.bold(content));
+
+  // Handle <i>content</i> - italic (dimmed as terminal alternative)
+  text = text.replace(/<i>([\s\S]*?)<\/i>/gi, (match, content) => chalk.italic(content));
+
+  // Handle <u>content</u> - underline
+  text = text.replace(/<u>([\s\S]*?)<\/u>/gi, (match, content) => chalk.underline(content));
+
+  // Handle <li>content</li> - list item with bullet
+  text = text.replace(/<li>([\s\S]*?)<\/li>/gi, (match, content) => `  • ${content.trim()}\n`);
+
+  // Handle <ul>content</ul> - unordered list (just preserve content, items will be formatted)
+  text = text.replace(/<ul>([\s\S]*?)<\/ul>/gi, (match, content) => `${content}\n`);
+
+  // Handle <p>content</p> - paragraph with spacing
+  text = text.replace(/<p>([\s\S]*?)<\/p>/gi, (match, content) => `${content.trim()}\n\n`);
+
+  // Handle <div>content</div> - block with newline
+  text = text.replace(/<div>([\s\S]*?)<\/div>/gi, (match, content) => `${content.trim()}\n\n`);
+
+  // Handle <pre>content</pre> - preformatted text with monospace styling
+  text = text.replace(/<pre>([\s\S]*?)<\/pre>/gi, (match, content) => {
+    // Preserve internal whitespace and newlines, apply dimmed styling for code-like appearance
+    const lines = content.split('\n');
+    const formattedLines = lines.map(line => chalk.dim(line));
+    return '\n' + formattedLines.join('\n') + '\n\n';
+  });
+
+  // Clean up any remaining HTML tags that weren't processed
+  text = text.replace(/<[^>]+>/g, '');
+
+  // Clean up excessive blank lines (more than 2 consecutive newlines)
+  text = text.replace(/\n{3,}/g, '\n\n');
+
+  // Trim extra whitespace at start and end
+  text = text.trim();
+
+  return text;
+}
+
+/**
+ * Render HTML and print to console
+ * @param {string} html - HTML string to render
+ */
+export function printHTML(html) {
+  console.log(renderHTML(html));
+}
Author	SHA1	Message	Date
sebseb7	863f45f666	chore: @modelcontextprotocol/sdk als Abhängigkeit hinzugefügt	2026-04-05 03:20:20 +02:00
sebseb7	38e702ec2f	feat: Zusammenfassung der endgültigen Antwort in zwei Schritten umgestaltet - Zerlegung von `summarizeFinalAnswer` in zwei separate LLM-Aufrufe: 1. Zusammenfassung, Quellen und vorgeschlagene Suchen 2. Anreicherung mit Emojis und HTML-Tags - Verbesserte Prompt-Formulierung für detailliertere Zusammenfassungen - Verwendung eines günstigeren Modells für den Formatierungsschritt - Hinzufügen separater Kostenprotokollierung pro Schritt - Aktualisierung der JSON-Schema-Antwortstruktur	2026-04-05 02:04:35 +02:00
sebseb7	92845a5a4c	feat: Füge Zusammenfassung der Suchergebnisse mit summarizeDetail hinzu - Neue Funktion summarizeDetail in openRouterService.js implementiert - Verwendet OpenRouter API direkt mit JSON-Schema-Antwortformat - Integriert die Zusammenfassung in searchService.js für detaillierte Inhalte - Filtert relevante Informationen aus den Suchergebnissen basierend auf der ursprünglichen Frage	2026-04-05 01:14:11 +02:00
sebseb7	88015fbcae	feat: UI-Verbesserungen und Model-Informationen in Kostenaufschlüsselung - Vorgeschlagene Folgesuchen im UI nach oben verschoben - Spalte "Modell" zur Kostenaufschlüsselungstabelle hinzugefügt - Modellnamen für OpenRouter-API-Aufrufe (Rephrase, Rank, Final Summary) ergänzt - Datenstruktur für Kostenaufschlüsselung um Modell-Information erweitert	2026-04-05 01:03:04 +02:00
sebseb7	e0a602135a	chore: Lokalisierung der UI-Texte ins Deutsche - Übersetzung aller statischen Texte in der Benutzeroberfläche von Englisch nach Deutsch - Inklusive Schaltflächen, Überschriften, Fehlermeldungen, Statusmeldungen und Tabellenüberschriften	2026-04-05 00:53:27 +02:00
sebseb7	5f26029cfe	feat: Vorschläge für Folgesuchen hinzufügen - CSS-Stile für vorgeschlagene Suchschaltflächen hinzugefügt - HTML-Container für die Anzeige vorgeschlagener Suchen hinzugefügt - Logik zur Darstellung und Interaktion mit vorgeschlagenen Suchen implementiert - OpenRouter-Prompt um Hinweis auf Folgesuchen erweitert - JSON-Schema um Feld 'suggestedSearches' ergänzt	2026-04-05 00:37:51 +02:00
sebseb7	d2920fd39a	token count for search	2026-04-04 21:51:52 +02:00
sebseb7	92b313fa79	cli html renderer	2026-04-04 16:51:00 +02:00
sebseb7	2e9a5e9e7f	cli	2026-04-04 16:33:33 +02:00
sebseb7	27180aa2c3	log	2026-04-04 15:13:02 +02:00