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Serper Search MCP Server

by NightTrek
GitHub
TypeScript
41
  • Apple
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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:

git clone https://github.com/yourusername/serper-search-server.git cd serper-search-server

  1. Install dependencies:

pnpm install

  1. Build the server:

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:

# 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 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

{ "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:

{ "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:

{ "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:

{ "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 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 file for details.

🙏 Acknowledgments

Deploy Server
A
security – no known vulnerabilities
-
license - not tested
A
quality - confirmed to work

How are these scores calculated?

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Enables integration of Google search functionality into MCP-enabled applications using the Serper API, providing rich search results, configurable parameters, and efficient response handling.

  1. ✨ Features
    1. 🚀 Installation
      1. ⚙️ Configuration
        1. 🔌 Integration
          1. Claude Desktop
        2. 🛠 Usage
          1. Search Tool
          2. Deep Research Tool
          3. Search Tool Example Response
        3. 🔍 Response Types
          1. Knowledge Graph
          2. Organic Results
          3. People Also Ask
          4. Related Searches
        4. 📊 Quality Metrics
          1. 🤝 Contributing
            1. 📝 License
              1. 🙏 Acknowledgments

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