documentation-search-mcp

anton-prosterity/documentation-search-mcp

3.3

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The Enhanced Documentation Search MCP Server is designed to streamline developer workflows by providing instant access to documentation, security analysis, and project generation tools.

The Enhanced Documentation Search MCP Server is a powerful tool that enhances developer productivity by automating complex tasks such as documentation search, security audits, and project setup. It integrates seamlessly with AI assistants, allowing developers to query and receive actionable insights in seconds. This server supports over 104 libraries, offering a comprehensive solution for multi-library searches, security comparisons, and learning path generation. By leveraging the Model Context Protocol (MCP), it ensures compatibility with various AI platforms, providing a robust and scalable solution for modern development environments. The server's AWS-style deployment model ensures zero local setup, automatic updates, and isolated environments, making it an ideal choice for both individual developers and enterprise teams.

Features

  • Multi-Lib Search: Search across 104+ documentation sources simultaneously.
  • Project Security: Scan dependencies for vulnerabilities with instant audit reports.
  • Project Generation: Create boilerplate code for new projects effortlessly.
  • Docker Environments: Set up local services like Postgres/Redis with ease.
  • Learning Paths: Generate structured learning plans for various technologies.

Usages

usage with Claude Desktop

{
  "mcpServers": {
    "documentation-search-enhanced": {
      "command": "uvx",
      "args": ["documentation-search-enhanced@latest"],
      "env": {
        "SERPER_API_KEY": "your_serper_api_key_here"
      }
    }
  }
}

usage with Cursor

{
  "mcpServers": {
    "documentation-search-enhanced": {
      "command": "uvx",
      "args": ["documentation-search-enhanced@latest"],
      "env": {
        "SERPER_API_KEY": "your_serper_api_key_here"
      }
    }
  }
}

Tools

  1. get_docs

    Fetches and summarizes documentation for one or more libraries.

  2. semantic_search

    Performs AI-powered semantic search across multiple libraries, ranking results by relevance.

  3. get_learning_path

    Generates a structured learning curriculum for a technology or skill level.

  4. get_code_examples

    Finds curated code examples for a specific topic.

  5. scan_project_dependencies

    Scans your project's dependencies for known security vulnerabilities.