🚀 Enhanced Documentation Search MCP Server

An enhanced MCP server for documentation search, security analysis, and developer productivity. Deploys instantly with uvx, just like official AWS MCP servers.

Key Features	Description	Example Query
📚 Multi-Lib Search	Search across 104+ docs simultaneously	`"Compare state management in react vs vue"`
🛡️ Project Security	Scan all dependencies for vulnerabilities	`"Are there any security issues in my project?"`
🏗️ Project Generation	Create boilerplate for new projects	`"Create a new fastapi project called my-api"`
🐳 Docker Environments	Set up local services like Postgres/Redis	`"Set up a postgres database for me"`
🎓 Learning Paths	Get a structured learning plan	`"Give me a learning path for devops"`
⚖️ Security Comparison	Compare security scores of libraries	`"Compare security of flask vs django"`

🚀 MCP Value Proposition: From Minutes to Seconds

To understand the impact of this MCP server, let's compare a common, critical developer task with and without the tool.

Scenario: "Are there any vulnerabilities in my project's dependencies?"

Without MCP (The Manual Grind)	With MCP (The Instant Audit)
1. Open your `pyproject.toml` or `requirements.txt`.	1. Ask your AI assistant:
2. For each of your 25 dependencies:	`Are there any vulnerabilities in my project?`
a. Google `"[library-name] vulnerability"`.
b. Open its PyPI page, look for warnings.
c. Open its GitHub page, find the "Security" tab.
d. Manually check if any listed CVEs apply to your specific version.
3. Try to mentally aggregate the risk level.
4. Miss one? Your project is still at risk.
---	---
*Time Required: 15-30 minutes*	*Time Required: ~5 seconds*
*Output: A vague sense of security and 20 open browser tabs.*	*Output: A precise, actionable JSON report.*
	`json { "summary": { "dependency_file": "pyproject.toml", "total_dependencies": 25, "vulnerable_count": 2, "overall_project_risk": "High" }, "vulnerable_packages": [ { "library": "requests", "version": "2.25.0", "security_score": 35, "summary": "High severity CVE found..." } ] }`

This is the core value: automating tedious, complex, and critical developer workflows to deliver instant, accurate, and actionable insights.

🎯 What This Does

Transforms your AI assistant into a documentation expert!

Instead of your AI assistant saying "I don't have access to current documentation", it now:

🔍 Searches live documentation from 104+ popular libraries.
📚 Returns current, accurate code examples.
🎯 Provides contextual recommendations based on your needs.
⚡ Caches results for lightning-fast follow-up questions.

🚀 AWS-Style Deployment Ready

This MCP server follows the exact same deployment pattern as AWS MCP servers:

# Just like AWS MCP servers - zero setup required!
uvx documentation-search-enhanced@latest

Same professional experience:

✅ No local cloning or setup
✅ Automatic dependency management
✅ Always up-to-date with @latest
✅ Works with any MCP-compatible AI assistant

🔧 Add to Your AI Assistant

For Cursor

Create .cursor/mcp.json in your project root:

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

For Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

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

That's it! 🎉 Your AI assistant now has development superpowers.

🛠️ Available Tools

A summary of the tools provided by this MCP server.

Tool	Description
`get_docs`	Fetches and summarizes documentation for one or more libraries.
`semantic_search`	Performs AI-powered semantic search across multiple libraries, ranking results by relevance.
`get_learning_path`	Generates a structured learning curriculum for a technology or skill level.
`get_code_examples`	Finds curated code examples for a specific topic.
`scan_project_dependencies`	(New!) Scans your project's dependencies for known security vulnerabilities.
`generate_project_starter`	(New!) Creates boilerplate for new FastAPI or React projects.
`manage_dev_environment`	(New!) Generates a `docker-compose.yml` for services like Postgres or Redis.
`get_security_summary`	Provides a quick security score and summary for a single library.
`compare_library_security`	Compares the security posture of multiple libraries side-by-side.
`suggest_libraries`	Autocompletes library names.
`health_check`	Checks the status of documentation sources.

🏠 Local Development (Optional)

If you want to contribute or customize:

git clone https://github.com/antonmishel/documentation-search-mcp.git
cd documentation-search-mcp
uv sync
echo "SERPER_API_KEY=your_key_here" > .env
uv run python src/documentation_search_enhanced/main.py

Project Structure

documentation-search-mcp/
├── src/
│   └── documentation_search_enhanced/
│       ├── __init__.py              # Package initialization
│       ├── main.py                  # Main MCP server implementation
│       ├── config.json              # Documentation sources configuration
│       ├── config_manager.py        # Environment-aware configuration
│       ├── vulnerability_scanner.py # Security vulnerability scanning
│       ├── project_scanner.py       # Scans project dependency files
│       ├── project_generator.py     # Generates project boilerplate
│       └── docker_manager.py        # Manages Docker environments
├── pyproject.toml                   # Project dependencies and packaging
├── publish_to_pypi.sh               # Publishing script
├── samples/                         # Usage examples and configs
├── CHANGELOG.md                     # Version history
└── README.md                        # This file

Contributing

Contributions are welcome! Please see CONTRIBUTING.md for details.

License

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

🎯 Quick Reference

Command	What It Does	Example
`uvx documentation-search-enhanced@latest`	Install/run MCP server	One-time setup
Get docs for library	Search documentation	"Find FastAPI authentication examples"
Get library suggestions	Auto-complete libraries	"What libraries start with 'lang'?"
Check system health	Monitor performance	"Check if documentation sources are working"
Compare technologies	Side-by-side analysis	"Compare FastAPI vs Django for APIs"

🔑 Supported Libraries (45+)

🔥 AI & ML: langchain, openai, anthropic, transformers, scikit-learn, spacy
🌐 Web Frameworks: fastapi, django, flask, express
⚛️ Frontend: react, svelte, javascript, typescript
☁️ Cloud: aws, google-cloud, azure, boto3
🐍 Python: pandas, numpy, matplotlib, requests, streamlit
🛠️ DevOps: docker, kubernetes
💾 Data: duckdb, jupyter, papermill

✨ Benefits of AWS-Style Deployment

✅ Zero Local Setup - No cloning, no path management
✅ Automatic Updates - Always get the latest version with @latest
✅ Isolated Environment - uvx handles dependencies automatically
✅ Universal Compatibility - Works with any MCP-compatible AI assistant
✅ No Maintenance - No local virtual environments to manage

🔄 Update to Latest Version

# The @latest tag automatically gets the newest version
# Just restart your AI assistant to get updates

🎯 Complete Enhancement Recommendations (Based on AWS MCP Analysis)

Based on my analysis of the AWS MCP repository, here are priority enhancements that would make your documentation-search-enhanced MCP server enterprise-grade:

✅ Already Implemented

Enhanced Configuration Management - Added AWS-style config with auto_approve, priority, features
Structured Logging - Created AWS-style logging with FASTMCP_LOG_LEVEL support
Samples Directory - Added comprehensive usage examples and configurations
Project-Aware Security Scan - Scans pyproject.toml, etc. for vulnerabilities.
Project Boilerplate Generation - Creates starter projects from templates.
Local Dev Environment Management - Generates docker-compose.yml for services.

🚀 High Priority Enhancements

7. Rate Limiting & Resource Management

# Add to main.py
from asyncio import Semaphore
from collections import defaultdict
from datetime import datetime, timedelta

class RateLimiter:
    def __init__(self, requests_per_minute: int = 60):
        self.requests_per_minute = requests_per_minute
        self.requests = defaultdict(list)
    
    async def check_rate_limit(self, identifier: str = "default"):
        now = datetime.now()
        # Implementation...

8. Auto-Approve Tool Integration

# Modify tools to respect auto-approve settings
@mcp.tool()
async def get_docs(query: str, library: str):
    """Enhanced with auto-approve support"""
    config = load_config()
    auto_approve = config["server_config"]["auto_approve"].get("get_docs", False)
    
    if not auto_approve:
        # Request user approval for external fetch
        pass

9. Enhanced Analytics & Metrics

# Add usage analytics like AWS MCP servers
class AnalyticsTracker:
    def __init__(self):
        self.metrics = {
            "requests_total": 0,
            "libraries_searched": defaultdict(int),
            "response_times": [],
            "error_count": 0
        }

10. Plugin Architecture

# Enable community extensions
class PluginManager:
    def __init__(self):
        self.plugins = []
    
    def register_plugin(self, plugin):
        self.plugins.append(plugin)
    
    async def execute_plugins(self, event_type: str, data: dict):
        for plugin in self.plugins:
            await plugin.handle(event_type, data)

🎯 Medium Priority Enhancements

11. Persistent Caching

# Add SQLite-based persistent cache
import sqlite3
import pickle

class PersistentCache(SimpleCache):
    def __init__(self, db_path: str = "cache.db"):
        super().__init__()
        self.db_path = db_path
        self._init_db()

12. Configuration Validation

# Add pydantic-based config validation
from pydantic import BaseModel, validator

class ServerConfig(BaseModel):
    name: str
    version: str
    logging_level: str = "INFO"
    max_concurrent_requests: int = 10
    
    @validator('logging_level')
    def validate_log_level(cls, v):
        if v not in ['ERROR', 'WARN', 'INFO', 'DEBUG']:
            raise ValueError('Invalid log level')
        return v

13. Health Check Enhancements

# Add comprehensive health monitoring
@mcp.tool()
async def detailed_health_check():
    """Enhanced health check with more metrics"""
    return {
        "status": "healthy",
        "uptime_seconds": (datetime.now() - start_time).total_seconds(),
        "memory_usage_mb": psutil.Process().memory_info().rss / 1024 / 1024,
        "cache_hit_rate": cache.get_hit_rate(),
        "active_connections": len(active_connections),
        "rate_limit_status": rate_limiter.get_status()
    }

📊 Advanced Features (AWS MCP Inspired)

14. Multiple Sub-Servers (Like AWS MCP Collection)

# Modular architecture
uvx documentation-search-enhanced.core@latest      # Core search
uvx documentation-search-enhanced.ai@latest        # AI-specific docs  
uvx documentation-search-enhanced.web@latest       # Web framework docs
uvx documentation-search-enhanced.cloud@latest     # Cloud platform docs

15. Environment-Specific Configurations

{
  "environments": {
    "development": {
      "logging_level": "DEBUG",
      "cache_ttl_hours": 1,
      "rate_limit_enabled": false
    },
    "production": {
      "logging_level": "ERROR", 
      "cache_ttl_hours": 24,
      "rate_limit_enabled": true
    }
  }
}

16. Advanced Search Features

@mcp.tool()
async def semantic_search(query: str, libraries: list[str], context: str = None):
    """AI-powered semantic search across multiple libraries"""

@mcp.tool() 
async def code_examples_search(query: str, language: str = "python"):
    """Search specifically for code examples"""

@mcp.tool()
async def trending_topics(category: str = "ai"):
    """Get trending topics in a category"""

🎉 Implementation Priority

Phase 1 (Done)

✅ Enhanced Configuration
✅ Structured Logging
✅ Samples Directory
✅ Project-Aware Security Scan
✅ Project Boilerplate Generation

Phase 2 (Done)

✅ Multi-Library Search

Phase 3 (Done)

✅ Local Dev Environment Management

Phase 4 (Next)

🔄 Rate Limiting Implementation
🔄 Auto-Approve Tool Integration
Analytics & Metrics Tracking

🚀 Expected Benefits

After implementing these AWS MCP-inspired enhancements:

🏢 Enterprise-Ready: Production-grade reliability and monitoring
🔒 Security: Rate limiting, auto-approve controls, audit trails
📈 Scalability: Plugin architecture, modular design, resource management
🛠️ Developer Experience: Better logging, samples, configuration validation
📊 Observability: Comprehensive metrics, health checks, performance tracking

Your MCP server would then match or exceed the capabilities of AWS MCP servers while maintaining the same professional deployment model! 🎯

Would you like me to implement any specific enhancement from this list?

🎯 Ready to Transform Your Development Workflow?

⭐ Star this repository if you find it valuable!

🚀 Get Started Now

Install: uvx documentation-search-enhanced@latest
API Key: Get free key from serper.dev
Configure: Add to your AI assistant (see Quick Start above)
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.

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! ⭐

@mcp.tool() async def semantic_search(query: str, libraries: list[str], context: str = None): """AI-powered semantic search across multiple libraries"""

@mcp.tool() async def code_examples_search(query: str, language: str = "python"): """Search specifically for code examples"""

@mcp.tool() async def trending_topics(category: str = "ai"): """Get trending topics in a category"""

Multi-Library Search

Get a broader perspective by searching across multiple libraries at once.

🤖 You: How do I handle state management in React vs Vue? (This will search both libraries and return a combined, ranked result)

Claude:

{
  "query": "state management",
  "libraries_searched": ["react", "vue"],
  "total_results": 20,
  "results": [
    {
      "source_library": "react",
      "title": "React Docs: State and Lifecycle",
      "relevance_score": 95.5,
      "snippet": "Learn how to use state and lifecycle methods in React components..."
    },
    {
      "source_library": "vue",
      "title": "Vue Docs: State Management with Pinia",
      "relevance_score": 92.1,
      "snippet": "Pinia is the now the official state management library for Vue..."
    },
    {
      "source_library": "react",
      "title": "Redux Toolkit Tutorial",
      "relevance_score": 88.7,
      "snippet": "The official, opinionated, batteries-included toolset for efficient Redux development..."
    }
  ]
}