Serper Search

A Model Context Protocol (MCP) server that enables web searching using the Serper API for Google search results.

Features

• Search the web using Serper API for Google search results
• Requires Serper API key for authentication
• Returns structured results with titles, URLs, and descriptions
• Fetches and includes actual web page content for each result
• Configurable number of results per search
• Supports streamable-http transport for LibreChat integration
• Docker containerization support
• Health checks and monitoring
• Built-in rate limiting to respect API limits

Installation

1. Clone or download this repository
2. Install dependencies:

npm install

3. Build the server:

npm run build

Usage Modes

Local Development (Stdio Mode)

For local development and direct MCP client integration:

npm start

Add the server to your MCP configuration:

For VSCode (Claude Dev Extension):

{
  "mcpServers": {
    "web-search": {
      "command": "node",
      "args": ["/path/to/web-search/build/index.js"]
    }
  }
}

For Claude Desktop:

{
  "mcpServers": {
    "web-search": {
      "command": "node",
      "args": ["/path/to/web-search/build/index.js"]
    }
  }
}

HTTP Mode (Container-Ready)

For containerized deployments or LibreChat integration:

# Start in HTTP mode
npm run start:http
# or
node build/index.js --http
# or set environment variable
MCP_HTTP_MODE=true npm start

The server will expose:

• MCP endpoint: http://localhost:3000/mcp (for JSON-RPC 2.0 requests)
• Health endpoint: http://localhost:3000/health
• Health check: http://localhost:3000/health

Docker Deployment

Using Docker directly:

# Build the image
npm run docker:build

# Run the container
npm run docker:run

Or manually:

docker build -t web-search-mcp .
docker run -p 3000:3000 -e MCP_HTTP_MODE=true web-search-mcp

Using Docker Compose:

# Start the service
npm run docker:up

# View logs
npm run docker:logs

# Stop the service
npm run docker:down

Container Configuration

Environment variables:

• MCP_HTTP_MODE: Set to true to enable HTTP/SSE mode
• PORT: Port number (default: 3000)
• SEARCH_RATE_LIMIT_MS: Minimum milliseconds between search requests (default: 500)

The container includes:

• Health checks
• Non-root user execution
• CORS support
• Automatic restart policies

Rate Limiting

The server includes built-in rate limiting to be respectful to Google's servers:

• Default: Minimum 500ms between search requests
• Configurable: Set SEARCH_RATE_LIMIT_MS environment variable
• Automatic: If requests come in faster than the limit, the server will automatically wait
• Logging: Rate limiting events are logged to stderr

Example with custom rate limit:

# Set 1 second minimum between searches
SEARCH_RATE_LIMIT_MS=1000 npm run start:http

API Reference

Tool: search

Parameters:

{
  "query": string,    // The search query
  "limit": number,    // Optional: Number of results to return (default: 5, max: 10)
  "maxContentLength": number  // Optional: Max length of content to extract (default: 50000)
}

Tool: fetch_page_content

Parameters:

{
  "url": string,    // The URL of the web page to fetch
  "maxContentLength": number  // Optional: Max length of content to extract (default: 50000)
}

HTTP/SSE API

Health Check

GET /health

Returns:

{
  "status": "ok",
  "service": "web-search-mcp"
}

SSE Connection

GET /sse

Establishes Server-Sent Events connection for real-time communication.

Message Endpoint

POST /message
Content-Type: application/json

{
  "jsonrpc": "2.0",
  "id": "unique-id",
  "method": "tools/call",
  "params": {
    "name": "search",
    "arguments": {
      "query": "your search query",
      "limit": 5
    }
  }
}

Testing

A test client is included (test-client.html) for testing the HTTP/SSE endpoint. Open it in a browser and ensure the server is running in HTTP mode.

Example Usage

MCP Client (stdio mode):

use_mcp_tool({
  server_name: "web-search",
  tool_name: "search",
  arguments: {
    query: "your search query",
    limit: 3
  }
})

HTTP API (container mode):

const response = await fetch('http://localhost:3000/message', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    jsonrpc: "2.0",
    id: "1",
    method: "tools/call",
    params: {
      name: "search",
      arguments: { query: "Model Context Protocol", limit: 5 }
    }
  })
});

Example response:

{
  "jsonrpc": "2.0",
  "id": "1",
  "result": {
    "content": [
      {
        "type": "text",
        "text": "[{\"title\":\"Example Result\",\"url\":\"https://example.com\",\"description\":\"Description...\"}]"
      }
    ]
  }
}

Fetch Page Content Tool

HTTP API Example

{
  "jsonrpc": "2.0",
  "id": "1",
  "method": "tools/call",
  "params": {
    "name": "fetch_page_content",
    "arguments": {
      "url": "https://en.wikipedia.org/wiki/Model_Context_Protocol",
      "maxContentLength": 10000
    }
  }
}

Example Response

{
  "jsonrpc": "2.0",
  "id": "1",
  "result": {
    "content": [
      {
        "type": "text",
        "text": "[Cleaned web page content here...]"
      }
    ]
  }
}

Limitations

Since this tool uses web scraping of Google search results, there are some important limitations to be aware of:

1. Rate Limiting: Google may temporarily block requests if too many searches are performed in a short time. To avoid this:

   • Keep searches to a reasonable frequency
   • Use the limit parameter judiciously
   • Consider implementing delays between searches if needed

2. Result Accuracy:

   • The tool relies on Google's HTML structure, which may change
   • Some results might be missing descriptions or other metadata
   • Complex search operators may not work as expected

3. Legal Considerations:

   • This tool is intended for personal use
   • Respect Google's terms of service
   • Consider implementing appropriate rate limiting for your use case

Contributing

Feel free to submit issues and enhancement requests!

License

This project is licensed under the MIT License. See the LICENSE file for details.