@deepbrainspace/serper-search-mcp NPM

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

To use the Serper Search MCP server, you can run it directly using npx or install it globally.

Using NPX (recommended for quick use): No installation step is needed. You can run the server directly (see "Usage with NPX" section below).

Global Installation (optional):

pnpm add -g @deepbrain/serper-search-mcp

Or using npm:

npm install -g @deepbrain/serper-search-mcp

⚙️ Configuration

Get your Serper API key from Serper.dev(https://serper.de
Create a .env file in the root directory where you run the server (e.g., when using npx):

# --- Required for basic search ---
SERPER_API_KEY=your_api_key_here

# --- Optional: LLM Configuration for Deep Research tool ---
# The Deep Research tool requires an LLM. Configure it using the variables below.
# If SERPER_LLM_API_KEY is not provided, the Deep Research tool will be unavailable.

SERPER_LLM_PROVIDER="google"  # Or "openrouter". Defaults to "google".
SERPER_LLM_API_KEY="your_llm_api_key_here" # Your API key for either Google (Gemini) or OpenRouter.
SERPER_LLM_MODEL=""           # Optional. Override the default model for the chosen provider.
                              # Default for Google: "gemini-2.0-flash-lite-preview-02-05"
                              # Default for OpenRouter: "google/gemini-flash-1.5" (or other suitable model)

# --- Optional: Advanced Quality Metrics Configuration ---
# (These are pre-configured by default)
# USAGE_METRICS_KEY=your-custom-metrics-key
# USAGE_PROJECT_ID=your-custom-project-id
# METRICS_ENDPOINT=https://your-custom-host.com
# DISABLE_METRICS=false # Not recommended

LLM Configuration Details:

SERPER_LLM_PROVIDER: Specifies the LLM provider.
- "google" (default): Uses Google Generative AI (Gemini models). SERPER_LLM_API_KEY should be your Google AI Studio API key.
- "openrouter": Uses OpenRouter. SERPER_LLM_API_KEY should be your OpenRouter API key.
SERPER_LLM_API_KEY: The API key for your chosen SERPER_LLM_PROVIDER.
SERPER_LLM_MODEL: (Optional) Specify a particular model to use. If not set, a default model for the chosen provider will be used:
- Google Default: gemini-2.0-flash-lite-preview-02-05
- OpenRouter Default: google/gemini-flash-1.5 (or another suitable model like mistralai/mistral-7b-instruct)
If SERPER_LLM_API_KEY is not provided, the Deep Research tool will be unavailable.

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": {
    "@deepbrain/serper-search-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@deepbrain/serper-search-mcp" // You can append @version like @0.2.0 if needed
      ],
      "env": {
        "SERPER_API_KEY": "your_serper_api_key_here",
        // For Deep Research tool (if needed):
        "SERPER_LLM_PROVIDER": "google",  // or "openrouter"
        "SERPER_LLM_API_KEY": "your_actual_llm_api_key",
        "SERPER_LLM_MODEL": "" // Optional: "gemini-2.5-pro-preview-05-06" or other model
        // "DEBUG": "true" // If your server uses this for more verbose logging
      }
    }
  }
}

If you installed it globally (e.g., pnpm add -g @deepbrain/serper-search-mcp), you might be able to use a simpler command, ensuring the environment variables are set in the MCP client's env block:

{
  "mcpServers": {
    "@deepbrain/serper-search-mcp": {
      "command": "serper-search-mcp", // This is the binary name from your package.json
      "env": {
        "SERPER_API_KEY": "your_serper_api_key_here",
        "SERPER_LLM_PROVIDER": "google", // or "openrouter"
        "SERPER_LLM_API_KEY": "your_actual_llm_api_key"
        // "SERPER_LLM_MODEL": "your_preferred_model" // Optional
      }
    }
  }
}

🛠 Usage with NPX

You can run the server directly from the command line using npx:

npx @deepbrain/serper-search-mcp

Make sure you have your .env file configured in the directory where you run this command, or set the environment variables (SERPER_API_KEY, etc.) in your shell.

If you have it installed globally, you can run:

serper-search-mcp

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

📊 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

Serper API for providing the Google search capabilities
Model Context Protocol for the MCP framework
PostHog for analytics capabilities

@google/generative-ai @modelcontextprotocol/sdk axios dotenv posthog-node uuid

0.2.1

7 months ago

@deepbrainspace/serper-search-mcp v0.2.1

Serper Search MCP Server

✨ Features

🚀 Installation

⚙️ Configuration

🔌 Integration

Claude Desktop

🛠 Usage with NPX

Search Tool

Search Tool

Deep Research Tool

Search Tool Example Response

🔍 Response Types

Knowledge Graph

Organic Results

People Also Ask

Related Searches

📊 Quality Metrics

🤝 Contributing

📝 License

🙏 Acknowledgments