Serper Search MCP Server

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A Model Context Protocol (MCP) 服务器,提供通过 Serper API 的谷歌搜索功能,以及一个由 AI 驱动的深度研究工具。需要在 .env 文件中的环境变量 SERPER_API_KEY 配置 Serper API 密钥。

Search & researchstdioCommunity

Repository-wide counts · Cached 2026-03-07

Overview

The Serper Search MCP Server MCP server is a publicly available project. Review the upstream repository for installation instructions, supported tools, compatibility, permissions, and current maintenance status.

Configuration

Configuration, transport, authentication, and runtime requirements vary by project. Open the repository before connecting and use the smallest set of credentials and permissions required.

Open the Serper Search MCP Server repository to read the latest documentation.

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Exa MCP 服务器

exa-labs

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一个模型上下文协议(MCP)服务器,允许像Claude这样的AI助手使用Exa AI Search API进行实时网页搜索、学术论文搜索、LinkedIn搜索等。需要通过环境变量EXA_API_KEY配置的Exa API密钥。

Tavily MCP 服务器

tavily-ai

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Tavily MCP 服务器是一个网页数据管理平台,提供搜索、提取、映射和爬取等工具。您可以: - **网页搜索**:使用实时网页搜索查找任何主题的最新信息 - **内容提取**:以 markdown 或文本格式从 URL 获取原始页面内容 - **网站爬取**:从 URL 开始爬取网站,提取内容并可配置深度 - **站点映射**:通过列出从基础 URL 开始的 URL 来映射网站结构 - **研究**:通过收集和整合多个来源的信息进行全面研究

Perplexity API Platform MCP Server

perplexityai

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The official MCP server implementation for the Perplexity API Platform, providing AI assistants with real-time web search, reasoning, and research capabilities through Sonar models and the Search API. Requires setting the PERPLEXITY_API_KEY environment variable for API access. Optional environment variables include PERPLEXITY_TIMEOUT_MS for request timeout and PERPLEXITY_PROXY for proxy configuration.

Perplexity Ask MCP Server

ppl-ai

Community

An MCP server implementation that integrates the Sonar API to provide Claude with unparalleled real-time, web-wide research. Requires setting the Sonar API key via the environment variable PERPLEXITY_API_KEY.

FROM THE SOURCE

Repository README

Build-time snapshot · Retrieved 2026-10-05

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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

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