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Serper Search MCP Server

by NightTrek
README.md6.52 kB
# Serper Search MCP Server A Model Context Protocol server that provides Google search capabilities through the Serper API, along with an AI-powered Deep Research tool. This server enables easy integration of search and research functionality into your MCP-enabled applications. ## ✨ Features - 🌐 Powerful Google search integration through Serper API - 🔄 Rich search response data including: - Knowledge Graph information - Organic search results - "People Also Ask" questions - Related searches - 🧠 AI-powered Deep Research tool: - Performs multi-step, iterative research - Generates sub-queries to explore topics thoroughly - Synthesizes information from multiple sources - Provides citations for all information - Adjustable research depth levels - Built-in quality metrics for continuous improvement - 🛠 Configurable search parameters: - Country targeting - Language selection - Result count customization - Autocorrect options - 🔒 Secure API key handling - ⚡️ Rate limiting and caching support - 📝 TypeScript support with full type definitions - 📊 Integrated performance metrics for result optimization ## 🚀 Installation 1. Clone the repository: ```bash git clone https://github.com/yourusername/serper-search-server.git cd serper-search-server ``` 2. Install dependencies: ```bash pnpm install ``` 3. Build the server: ```bash pnpm run build ``` ## ⚙️ Configuration 1. Get your Serper API key from [Serper.dev](https://serper.de 2. Create a `.env` file in the root directory: ```env # Required SERPER_API_KEY=your_api_key_here # Optional - Advanced Quality Metrics Configuration (pre-configured by default) USAGE_METRICS_KEY=your-custom-metrics-key # Optional USAGE_PROJECT_ID=your-custom-project-id # Optional METRICS_ENDPOINT=https://your-custom-host.com # Optional DISABLE_METRICS=false # Not recommended ``` See [TELEMETRY.md](TELEMETRY.md) for detailed information about: - Quality metrics collection - Performance monitoring - Usage analytics - Dashboard setup - Continuous improvement ## 🔌 Integration ### Claude Desktop Add the server config to your Claude Desktop configuration: **MacOS**: `~/Library/Application Support/Claude/claude_desktop_config.json` **Windows**: `%APPDATA%/Claude/claude_desktop_config.json` ```json { "mcpServers": { "serper-search-server": { "command": "/path/to/serper-search-server/build/index.js", "env": { "SERPER_API_KEY": "your_api_key_here" } } } } ``` ## 🛠 Usage ### Search Tool The server provides a powerful search tool with the following parameters: ```typescript { "query": string, // Search query "numResults"?: number, // Number of results (default: 10, max: 100) "gl"?: string, // Country code (e.g., "us", "uk") "hl"?: string, // Language code (e.g., "en", "es") "autocorrect"?: boolean, // Enable autocorrect (default: true) "type"?: "search" // Search type (more types coming soon) } ``` ### Deep Research Tool For more comprehensive research needs, the server provides a deep research tool that performs multi-step research with the following parameters: ```typescript { "query": string, // Research query or question "depth"?: "basic" | "standard" | "deep", // Research depth (default: "standard") "maxSources"?: number // Maximum sources to include (default: 10) } ``` The deep research tool: - Breaks down complex queries into focused sub-queries - Executes multiple searches to gather comprehensive information - Uses AI to synthesize information from multiple sources - Formats results with proper citations and references - Adapts its research strategy based on intermediate results - Collects anonymous quality metrics to improve search results Depth Levels: - basic: Quick overview (3-5 sources, ~5 min) Good for: Simple facts, quick definitions, straightforward questions - standard: Comprehensive analysis (5-10 sources, ~10 min) Good for: Most research needs, balanced depth and speed - deep: Exhaustive research (10+ sources, ~15-20 min) Good for: Complex topics, academic research, thorough analysis ### Search Tool Example Response The search results include rich data: ```json { "searchParameters": { "q": "apple inc", "gl": "us", "hl": "en", "autocorrect": true, "type": "search" }, "knowledgeGraph": { "title": "Apple", "type": "Technology company", "website": "http://www.apple.com/", "description": "Apple Inc. is an American multinational technology company...", "attributes": { "Headquarters": "Cupertino, CA", "CEO": "Tim Cook (Aug 24, 2011–)", "Founded": "April 1, 1976, Los Altos, CA" } }, "organic": [ { "title": "Apple", "link": "https://www.apple.com/", "snippet": "Discover the innovative world of Apple...", "position": 1 } ], "peopleAlsoAsk": [ { "question": "What does Apple Inc mean?", "snippet": "Apple Inc., formerly Apple Computer, Inc....", "link": "https://www.britannica.com/topic/Apple-Inc" } ], "relatedSearches": [ { "query": "Who invented the iPhone" } ] } ``` ## 🔍 Response Types ### Knowledge Graph Contains entity information when available: - Title and type - Website URL - Description - Key attributes ### Organic Results List of search results including: - Title and URL - Snippet (description) - Position in results - Sitelinks when available ### People Also Ask Common questions related to the search: - Question text - Answer snippet - Source link ### Related Searches List of related search queries users often make. ## 📊 Quality Metrics The Deep Research tool includes integrated quality metrics: - Research process metrics - Performance monitoring - Issue tracking - Usage patterns - Result quality indicators See [TELEMETRY.md](TELEMETRY.md) for detailed information about the metrics collected to improve search quality. ## 🤝 Contributing Contributions are welcome! Please feel free to submit a Pull Request. ## 📝 License This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. ## 🙏 Acknowledgments - [Serper API](https://serper.dev) for providing the Google search capabilities - [Model Context Protocol](https://github.com/modelcontextprotocol/mcp) for the MCP framework - [PostHog](https://posthog.com) for analytics capabilities

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