anton-prosterity/documentation-search-mcp
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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.
š 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 |
---|---|---|
š Multi-Lib Search | Search across 104+ docs simultaneously | "Compare state management in react vs vue" |
š”ļø Project Security | Scan all dependencies for vulnerabilities | "Are there any security issues in my project?" |
šļø Project Generation | Create boilerplate for new projects | "Create a new fastapi project" |
š³ Docker Environments | Set up local services like Postgres/Redis | "Set up a postgres database for me" |
š Learning Paths | Get a structured learning plan | "Give me a learning path for devops" |
āļø Security Comparison | Compare security scores of libraries | "Compare flask vs django" |
š 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? |
Ā Ā Ā a. Google "[library-name] vulnerability" . | |
Ā Ā Ā b. Open its PyPI page, look for warnings. | |
Ā Ā Ā c. Open its GitHub page, find the "Security" tab. | |
Ā Ā Ā d. Manually check if CVEs apply to your version. | |
3. Try to mentally aggregate the risk level. | |
--- | --- |
Time Required: 15-30 minutes | Time Required: ~5 seconds |
Output: A vague sense of security. | Output: A precise, actionable JSON report. |
json { "summary": { "vulnerable_count": 2, "overall_project_risk": "High" }, "vulnerable_packages": [ { "library": "requests", "security_score": 35 } ] } |
This is the core value: automating tedious, complex, and critical developer workflows to deliver instant, accurate, and actionable insights.
š Quick Start
1. Install & Run
# No git clone required! Needs Python 3.12+
uvx documentation-search-enhanced@latest
2. Configure with your AI Assistant
Add to your Claude Desktop or Cursor configuration:
{
"mcpServers": {
"documentation-search-enhanced": {
"command": "uvx",
"args": ["documentation-search-enhanced@latest"],
"env": {
"SERPER_API_KEY": "your_serper_api_key_here"
}
}
}
}
š ļø Available Tools
This server provides a powerful suite of tools to enhance your development workflow:
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 (pyproject.toml , etc.) 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. |
get_current_config | (New!) Returns the active configuration, which you can save and modify for local overrides. |
health_check | Checks the status of documentation sources. |
āļø Customization
You can customize the server by creating a config.json
file in your project directory.
- Get the default config: Ask your AI assistant,
"get the current configuration"
. - Save as
config.json
: Save the output to aconfig.json
file in your project's root. - Modify: Add your own private documentation URLs or change settings.
The server will automatically use your local config.json
if it exists.
š Local Development
If you want to contribute or customize the server's code:
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
Contributing
Contributions are welcome! Please see for details.
License
This project is open source under the MIT License. See for details.
šÆ 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" |
š Supported Libraries (45+)
š„ AI & ML: langchain, openai, anthropic, transformers, scikit-learn, spacy
š Web Frameworks: fastapi, django, flask, express
āļø Frontend: react, svelte, javascript, typescript
āļø Cloud: aws, google-cloud, azure, boto3
š Python: pandas, numpy, matplotlib, requests, streamlit
š ļø DevOps: docker, kubernetes
š¾ Data: duckdb, jupyter, papermill
⨠Benefits of AWS-Style Deployment
ā
Zero Local Setup - No cloning, no path management
ā
Automatic Updates - Always get the latest version with @latest
ā
Isolated Environment - uvx
handles dependencies automatically
ā
Universal Compatibility - Works with any MCP-compatible AI assistant
ā
No Maintenance - No local virtual environments to manage
š Update to Latest Version
# The @latest tag automatically gets the newest version
# Just restart your AI assistant to get updates
šÆ 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:
ā 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. - Configuration Validation - Ensures
config.json
is valid on startup, providing clear errors.
š High Priority Enhancements
8. 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...
9. 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
10. 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
}
11. 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)
šÆ Medium Priority Enhancements
12. 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()
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()
}
š 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"""
š Implementation Priority
Phase 1 (Done)
- ā Enhanced Configuration
- ā Structured Logging
- ā Samples Directory
- ā Project-Aware Security Scan
- ā Project Boilerplate Generation
Phase 2 (Done)
- ā Multi-Library Search
Phase 3 (Done)
- ā Local Dev Environment Management
Phase 4 (Current)
- ā Configuration Validation
- š Rate Limiting Implementation
- š Auto-Approve Tool Integration
- Analytics & Metrics Tracking
š Expected Benefits
After implementing these AWS MCP-inspired enhancements:
- š¢ Enterprise-Ready: Production-grade reliability and monitoring
- š Security: Rate limiting, auto-approve controls, audit trails
- š Scalability: Plugin architecture, modular design, resource management
- š ļø Developer Experience: Better logging, samples, configuration validation
- š 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! šÆ
Would you like me to implement any specific enhancement from this list?
šÆ Ready to Transform Your Development Workflow?
ā Star this repository if you find it valuable!
š 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?"
š¤ Join the Community
- š¬ Questions? Open an issue
- š Bug Reports: We fix them fast!
- ⨠Feature Requests: Your ideas make this better
- š Pull Requests: Contributions welcome!
š License
This project is open source under the MIT License. See file for details.
Made with ā¤ļø by developers, for developers
Transform Claude into your personal development advisor today!
ā Don't forget to star this repo if it helped you! ā
@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.
š¤ 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..."
}
]
}
š New in Version 1.2: Project-Aware Tools
Project Security Audit
Configuration
Your MCP server comes pre-configured with 104 popular libraries, but you can easily customize it.
How to Customize Your Configuration
-
Get the Default Configuration: Ask your AI assistant:
"Show me the current configuration"
This will output the entireconfig.json
content. -
Create a Local
config.json
:- Save the output from the previous step into a file named
config.json
in your project's root directory.
- Save the output from the previous step into a file named
-
Modify Your Local Config:
- Add your own private documentation URLs, internal libraries, or tweak any settings.
The MCP server will automatically detect and use your local config.json
instead of the default one.
Adding New Documentation Sources
To add a new library, simply edit your local config.json
and add a new entry to the docs_urls
and categories
sections: