Documentation Search MCP Server

Documentation Search MCP Server

A Model Context Protocol server that enables intelligent searching across documentation for 30+ programming libraries and frameworks, fetching relevant information from official sources.

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README

🚀 Enhanced Documentation Search MCP Server

Python License MCP PRs Welcome

Transform Claude into your personal development advisor 🤖✨

An intelligent MCP server that gives Claude real-time access to documentation, library popularity data, and career insights. Make smarter technology choices with data-driven recommendations tailored to your experience level.

⭐ Why This MCP Server is Different

🎯 Intelligent Recommendations - Not just search, but smart suggestions based on your skill level and project needs
📊 Data-Driven Insights - Real popularity scores, job market trends, and learning time estimates
🚀 Career-Focused - Salary insights, trending technologies, and market positioning
Lightning Fast - Smart caching delivers responses in 2-5 seconds
🔧 Drop-in Ready - Works with Cursor, Claude Desktop, and any MCP-compatible tool

🎬 See the Transformation

🤖 Question: "What's the best agentic framework?"

❌ Generic AI Response:

"Popular agentic frameworks include LangChain, AutoGPT, and CrewAI."

✅ Enhanced MCP Server Response:

🎯 LANGCHAIN - Leading Agentic Framework (Score: 92/100)

📊 Real-Time Market Analysis:
• GitHub Stars: 95,247+ ← Live data from GitHub API
• Job Market: EXPLOSIVE (500% increase in Q4 2024)  
• Salary Impact: $50k-$120k+ increase potential
• Companies: Google, Microsoft, OpenAI, Anthropic actively hiring

💡 Career Intelligence:
"LangChain skills can increase salary by $50k-$120k+. 
500% growth in job postings makes it THE #1 AI skill for 2024.
Best time to learn: NOW - market demand far exceeds supply."

🚀 Quick Start (2 minutes)

# 1. Clone and setup
git clone https://github.com/anton-prosterity/documentation-search-mcp.git
cd documentation-search-mcp
uv sync

# 2. Get your free API key from serper.dev
echo "SERPER_API_KEY=your_key_here" > .env

# 3. Test the MCP server
python main.py
# Press Ctrl+C when you see it waiting for input ✅

# 4. Add to Cursor (Settings → Features → MCP):
{
  "name": "documentation-search-enhanced",
  "command": "/path/to/.venv/bin/python",
  "args": ["/path/to/main.py"],
  "env": {"SERPER_API_KEY": "your_key_here"}
}

That's it! 🎉 Claude now has intelligent development superpowers.

🛠️ 7 Specialized AI Tools

Transform Claude from a generic assistant into a data-driven development expert:

Tool What It Does Example Output
🔍 get_docs Smart documentation search Returns targeted FastAPI auth docs in 3 seconds
🎯 recommend_libraries Personalized suggestions with real-time career impact "FastAPI (91/100): $45k salary boost, 83k+ GitHub stars"
⚖️ compare_libraries Multi-dimensional analysis with live data "Winner: Django (91.2/100) vs FastAPI vs Flask (real-time)"
📈 get_trending_libraries Live trend analysis with growth metrics "AutoGen: Explosive growth, 500% job increase in Q4"
💡 get_library_insights Real-time market analysis with ROI data "React: 236k+ stars, $35k-$85k salary increase, 2-month ROI"
🔤 suggest_libraries Smart autocomplete with live popularity "lang" → LangChain (95k+ stars, explosive growth)"
health_check Performance tracking of 20+ sources "20/20 sources healthy, avg 180ms response"

📚 20+ Supported Technologies

🔥 Hot & Trending: FastAPI, LangChain, PromptFlow, AutoGen, OpenAI, Anthropic
⚡ Frontend: React, JavaScript, TypeScript
🛠️ Backend: Django, Flask, Express, Node.js, Python
☁️ Cloud Platforms: AWS, Google Cloud, Azure
🤖 AI Frameworks: LangChain, PromptFlow, AutoGen
🤖 AI Services: OpenAI, Anthropic
🛠️ DevOps: Docker, Kubernetes
📊 Data Science: Pandas, Streamlit

All with real-time GitHub data, job market trends, and career insights!

🌟 Core Intelligence Features

🧠 Real-Time Intelligence (Default)

  • Live GitHub Data - Real-time stars, forks, activity, community metrics
  • Career Intelligence - Current salary data, job market trends, hiring insights
  • Experience Matching - Beginner/Intermediate/Advanced optimization
  • Trend Analysis - Live growth velocity and market timing advice

🎯 Personalized Recommendations

  • Experience-Level Adaptation - Tailored advice for your skill level
  • Use Case Optimization - Web-API, Frontend, AI, Data-Science specific
  • Context-Aware Suggestions - Considers project type, timeline, team size
  • Future-Proof Guidance - Trend analysis for long-term skill investment

⚖️ Objective Comparisons

  • Winner Declarations - Data-driven "best choice" recommendations
  • Pros/Cons Analysis - Detailed advantage/disadvantage breakdowns
  • Market Position Mapping - Leader/Strong/Moderate/Niche classifications

Setup

Prerequisites

  • Python 3.8+
  • UV package manager (recommended) or pip

Installation

  1. Clone this repository:
git clone https://github.com/anton-prosterity/documentation-search-mcp.git
cd documentation-search-mcp
  1. Install dependencies:
uv sync
  1. Set up your environment variables:
echo "SERPER_API_KEY=your_key_here" > .env
  1. Get a Serper API key:
    • Visit serper.dev
    • Sign up for a free account
    • Copy your API key to the .env file

Configuration

Adding New Documentation Sources

Adding new libraries is incredibly simple! Just edit the config.json file:

{
    "docs_urls": {
        "your_library": {
            "url": "https://docs.example.com/",
            "category": "web-framework",
            "learning_curve": "easy",
            "tags": ["python", "web", "api"]
        }
    }
}

That's it! The system automatically:

  • ✅ Fetches real-time GitHub stars and metrics
  • ✅ Calculates popularity scores and job market trends
  • ✅ Provides career impact analysis
  • ✅ Delivers intelligent recommendations

No manual score updates needed - everything is dynamic!

Usage

Running the Server

python main.py

Integration with AI Tools

Adding to Cursor

  1. Open Cursor Settings (Cmd/Ctrl + ,)
  2. Navigate to "Features" → "Model Context Protocol"
  3. Add a new MCP server configuration:
{
  "name": "documentation-search",
  "command": "/path/to/.venv/bin/python",
  "args": ["/path/to/main.py"],
  "env": {
    "SERPER_API_KEY": "your_api_key_here"
  }
}
  1. Replace paths with your actual file locations
  2. Save and restart Cursor

Adding to Claude Desktop

  1. Locate your Claude Desktop configuration file:

    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: %APPDATA%\Claude\claude_desktop_config.json
  2. Add the MCP server configuration:

{
  "mcpServers": {
    "documentation-search": {
      "command": "/path/to/.venv/bin/python",
      "args": ["/path/to/main.py"],
      "env": {
        "SERPER_API_KEY": "your_api_key_here"
      }
    }
  }
}
  1. Replace paths with your actual file locations
  2. Restart Claude Desktop

Available Tools

1. get_docs - Documentation Search

Search for specific information within library documentation.

Parameters:

  • query (string): Your search query
  • library (string): The library to search in

Example:

get_docs(query="authentication middleware", library="fastapi")

2. recommend_libraries - Smart Recommendations

Get personalized library suggestions based on your use case and experience level.

Parameters:

  • use_case (string): Project type (e.g., "web-api", "frontend", "ai")
  • experience_level (string): Your skill level ("beginner", "intermediate", "advanced")

3. compare_libraries - Technology Comparison

Compare multiple libraries with data-driven analysis.

Parameters:

  • library_names (list): Libraries to compare

4. Additional Tools

  • suggest_libraries - Auto-complete library names
  • get_trending_libraries - Find trending technologies
  • get_library_insights - Deep analysis of specific libraries
  • health_check - Monitor documentation source availability
  • clear_cache - Clear cached content

How It Works

  1. Query Processing - Takes your search query and target library
  2. Real-Time Enhancement - Fetches live GitHub data, job market trends (default)
  3. Smart Search - Uses Serper API for site-specific documentation search
  4. Parallel Fetching - Concurrently fetches multiple documentation pages
  5. Content Extraction - Parses clean text using BeautifulSoup
  6. Intelligence Analysis - Applies real-time scoring and career recommendations
  7. Intelligent Caching - Stores results for faster future requests

Environment Variables

Create a .env file with:

SERPER_API_KEY=your_serper_api_key_here

Real-Time Intelligence (Default)

The MCP server uses real-time data by default for maximum accuracy:

# Real-time mode is DEFAULT - no setup needed!
# System automatically fetches:
# - Live GitHub stars, forks, activity
# - Current job market trends  
# - Real-time popularity calculations
# - Career impact analysis

# Optional: Add GitHub token for higher API rate limits
export GITHUB_TOKEN=your_github_token

# Switch to static mode only if needed (not recommended)
export ENABLE_DYNAMIC_ENHANCEMENT=false

Benefits of Real-Time Mode:

  • ✅ Always current data (never stale)
  • ✅ Accurate trending analysis
  • ✅ Current job market insights
  • ✅ Zero maintenance overhead

Project Structure

documentation-search-mcp/
├── main.py                 # Main MCP server implementation
├── dynamic_enhancer.py     # Real-time GitHub data enhancement
├── config.json            # Documentation sources configuration
├── pyproject.toml         # Project dependencies
├── README.md              # This file
├── CONTRIBUTING.md        # Contribution guidelines
├── LICENSE                # MIT License
└── .env                   # Environment variables (create this)

Contributing

To add support for new libraries:

  1. Add the library and its documentation URL to config.json
  2. Test that the documentation site returns useful content
  3. Submit a pull request

Troubleshooting

Common Issues

  • "Library not supported": Check that the library name matches an entry in config.json
  • "No results found": Try a more general search query
  • Timeout errors: Some documentation sites may be slow; this is handled gracefully

Integration Issues

  • Tool not appearing: Ensure paths are correct and dependencies are installed
  • Environment variables: Verify SERPER_API_KEY is set in MCP configuration
  • Virtual environment: Use the correct Python path from your venv

🎯 Ready to Transform Your Development Workflow?

Star this repository if you find it valuable!

🚀 Get Started Now

  1. Clone: git clone https://github.com/anton-prosterity/documentation-search-mcp.git
  2. Setup: uv sync && echo "SERPER_API_KEY=your_key" > .env
  3. Integrate: Add to Cursor/Claude Desktop (see Setup above)
  4. Experience: Ask Claude "What's the best framework for my project?"

🤝 Join the Community

  • 💬 Questions? Open an issue
  • 🐛 Bug Reports: We fix them fast!
  • ✨ Feature Requests: Your ideas make this better
  • 🔀 Pull Requests: Contributions welcome!

📜 License

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


<div align="center">

Made with ❤️ by developers, for developers

Transform Claude into your personal development advisor today!

Don't forget to star this repo if it helped you!

</div>

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