Free Mcp Search Server

A zero-API-key web search server built with MCP (Model Context Protocol) and Flask. No registration, no API keys, completely free.

Features

• MCP Protocol Support - Works with Claude Desktop and other MCP-compatible clients
• REST API - HTTP endpoints for easy integration
• Free Search - Uses DuckDuckGo (no API key required)
• Content Extraction - Extract text, links, and images from any webpage
• Batch Search - Search multiple queries at once
• Built-in Caching - 5-minute cache for faster responses
• CORS Enabled - Works with any frontend

Quick Start

Option 1: Run with Docker (Recommended)

# Build the image
docker build -t free-mcp-search .

# Run the container
docker run -p 8080:8080 free-mcp-search

Option 2: Run with Python

# Install dependencies
pip install -r requirements.txt

# Run the server
python mcp_server.py

The server starts on http://localhost:8080

REST API Usage

Web Search

curl "http://localhost:8080/api/search?query=python%20tutorial&num_results=5"

Extract Page Content

curl "http://localhost:8080/api/extract?url=https://example.com"

Batch Search

curl -X POST http://localhost:8080/api/batch \
  -H "Content-Type: application/json" \
  -d '{"queries": ["AI news", "Python tips", "Tech trends"], "num_results": 5}'

News Search

curl "http://localhost:8080/api/news?query=technology"

Health Check

curl http://localhost:8080/api/health

MCP Server Setup

For Claude Desktop

Add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "free-web-search": {
      "command": "python",
      "args": ["/path/to/mcp_server.py", "--mcp"],
      "env": {}
    }
  }
}

Or using Docker:

{
  "mcpServers": {
    "free-web-search": {
      "command": "docker",
      "args": ["run", "--rm", "-i", "free-mcp-search", "python", "mcp_server.py", "--mcp"]
    }
  }
}

MCP Tools Available

Tool	Description
web_search	Search the web, returns title, URL, snippet, domain
get_page_content	Extract content from a webpage
batch_search	Perform multiple searches at once
search_news	Search for recent news articles

Environment Variables

Variable	Default	Description
FLASK_PORT	8080	Server port
MAX_RESULTS	20	Maximum search results
CACHE_TTL	300	Cache TTL in seconds

API Response Examples

Search Response

{
  "query": "python tutorial",
  "count": 5,
  "results": [
    {
      "title": "Python Tutorial - W3Schools",
      "url": "https://www.w3schools.com/python/",
      "snippet": "Python is a widely used general-purpose programming language...",
      "domain": "www.w3schools.com"
    }
  ]
}

Extraction Response

{
  "url": "https://example.com",
  "title": "Example Domain",
  "content": "Example Domain This domain is for use in illustrative examples...",
  "links": ["https://www.iana.org/domains/example"],
  "images": []
}

Architecture

┌─────────────────────────────────────────────────────┐
│                    Client                           │
└─────────────────────┬───────────────────────────────┘
                      │
        ┌─────────────┴─────────────┐
        ▼                           ▼
┌───────────────┐           ┌───────────────┐
│  MCP Client  │           │  REST Client  │
└───────┬───────┘           └───────┬───────┘
        │                           │
        ▼                           ▼
┌─────────────────────────────────────────────────────┐
│              FreeMCP Search Server                   │
│  ┌─────────────┐  ┌─────────────────────────────────┐│
│  │ MCP Server │  │         Flask REST API          ││
│  │   (mcp)    │  │  /api/search, /api/extract, etc ││
│  └─────────────┘  └─────────────────────────────────┘│
│                      │                              │
│                      ▼                              │
│  ┌─────────────────────────────────────────────────┐│
│  │           Search Backend (DuckDuckGo)           ││
│  │  • Instant Answer API                            ││
│  │  • HTML Search Fallback                          ││
│  └─────────────────────────────────────────────────┘│
└─────────────────────────────────────────────────────┘

Deployment

Deploy to Railway

1. Create a new Railway project
2. Connect your GitHub repo
3. Railway auto-detects Dockerfile
4. Deploy!

Deploy to Render

1. Create a new Web Service
2. Connect your GitHub repo
3. Set build command: pip install -r requirements.txt
4. Set start command: gunicorn mcp_server:app
5. Deploy!

Deploy to Fly.io

fly launch
fly deploy

Rate Limits

• 100 requests per minute per IP (REST API)
• MCP has no strict rate limit
• Built-in caching reduces redundant requests

License

MIT License - Use freely for any purpose.

Contributing

Contributions welcome! Please open an issue or PR.