Brsearch MCP Server

🚀 URL Text Fetcher MCP Server

A modern Model Context Protocol (MCP) server that offers URL text fetching, web scraping, and web search capabilities. It uses the FastMCP framework and is designed for use with LM Studio and other MCP-compatible clients.

The server is built using the modern FastMCP framework, which provides the following advantages:

• Clean decorator-based tool definitions
• Automatic schema generation from type hints
• Simplified server setup and configuration
• Better error handling and logging

All security features and functionality have been preserved while modernizing to follow MCP best practices.

✨ Features

This MCP server enables AI models to:

• Fetch text content: Extract all visible text from any URL.
• Extract links: Discover related resources by extracting links from web pages.
• Search the web: Use Brave Search to search the web and automatically fetch content from top results.
• Handle errors gracefully: Employ proper timeout and exception handling.

🔒 Security Features

Enterprise-grade security implementation:

• SSRF Protection: Blocks requests to internal networks and metadata endpoints.
• Input Sanitization: Validates and cleans all URL and query inputs.
• Memory Protection: Content size limits prevent memory exhaustion.
• Rate Limiting: Thread-safe API rate limiting with configurable thresholds.
• Error Handling: Comprehensive exception handling without information leakage.

🛠️ Tools

The server provides three main tools:

fetch_url_text

• Description: Downloads all visible text from a URL.
• Parameters:
  • url (string, required): The URL to fetch text from.
• Returns: Clean text content from the webpage.

fetch_page_links

• Description: Extracts all links from a web page.
• Parameters:
  • url (string, required): The URL to fetch links from.
• Returns: List of all href links found on the page.

brave_search_and_fetch

• Description: Search the web using Brave Search and automatically fetch content from the top results.
• Parameters:
  • query (string, required): The search query.
  • max_results (integer, optional): Maximum number of results to fetch content for (default: 3, max: 10).
• Returns: Search results with full text content from each result URL.

📋 Prerequisites

Brave Search API Key

To use the search functionality, you'll need a free Brave Search API key:

1. Visit Brave Search API.
2. Sign up for a free account (2,000 queries/month, max 1 per second).
3. Get your API key.
4. Copy .env.example to .env and add your API key:

   cp .env.example .env
   # Edit .env and set: BRAVE_API_KEY=your_actual_api_key
   

📦 Installation

1. Clone this repository.
2. Install dependencies:

   uv sync --dev --all-extras
   

3. Configure your environment:

   cp .env.example .env
   # Edit .env file and set your BRAVE_API_KEY
   

💻 Usage Examples

With LM Studio

1. Open LM Studio and navigate to the Integrations section.
2. Click "Install" then "Edit mcp.json".

FastMCP Implementation (Recommended)

3. Option A: Use the configuration helper script

   ./configure_lmstudio_fastmcp.sh
   

   This will generate the correct configuration with the right paths for your system.

4. Option B: Manual configuration - Add the server configuration:

{
  "mcpServers": {
    "url-text-fetcher-fastmcp": {
      "command": "uv",
      "args": [
        "run", 
        "url-text-fetcher-fastmcp"
      ],
      "cwd": "/Users/wallison/TechProjects/mcp-server"
    }
  }
}

Legacy Implementation (Low-Level)

For the legacy implementation:

./configure_lmstudio.sh  # Generates config for legacy server

Note: The API key will be automatically loaded from your .env file in the project directory.

5. Save the configuration and restart LM Studio.
6. The server will appear in the Integrations section.

Standalone Usage

You can also run the server directly:

# FastMCP implementation (recommended)
uv run url-text-fetcher-fastmcp

# Legacy implementation
uv run url-text-fetcher

Basic Usage

Once configured with LM Studio, you can ask the AI to perform the following tasks:

• "Fetch the text content from https://example.com"
• "Get all the links from https://news.example.com"
• "Search for 'Python web scraping' and show me the content from the top 3 results"
• "What's the latest news about AI? Search and get the full articles"
• "Find information about MCP servers and fetch the detailed content"

📚 Documentation

Dependencies

• mcp>=1.12.3 - Model Context Protocol framework
• requests>=2.31.0 - HTTP library for web requests and Brave Search API
• beautifulsoup4>=4.12.0 - HTML parsing and text extraction

Configuration

The server can be configured via the .env file:

# Required: Brave Search API Key
BRAVE_API_KEY=your_api_key_here

# Brave Search API Rate Limit (requests per second)
# Free tier: 1 request per second (default)
# Paid tier: 20 requests per second  
# Higher tier: 50 requests per second
# Set this to match your subscription level
BRAVE_RATE_LIMIT_RPS=1

# Optional: Request timeout in seconds (default: 10)
REQUEST_TIMEOUT=10

# Optional: Content length limit in characters (default: 5000)
CONTENT_LENGTH_LIMIT=5000

# Optional: Maximum response size in bytes (default: 10MB)
MAX_RESPONSE_SIZE=10485760

Brave Search Subscription Tiers

The server automatically adjusts its rate limiting based on your Brave Search subscription:

• Free Tier: 1 request per second (BRAVE_RATE_LIMIT_RPS=1)
• Paid Tier: 20 requests per second (BRAVE_RATE_LIMIT_RPS=20)
• Higher Tier: 50 requests per second (BRAVE_RATE_LIMIT_RPS=50)

The server will enforce the configured rate limit across all concurrent requests to ensure you stay within your API quota. See .env.example for a template.

🔧 Technical Details

Development

This project uses:

• Python 3.13+
• uv for dependency management
• MCP SDK for protocol implementation

To set up for development:

1. Clone the repository.
2. Run uv sync --dev --all-extras.
3. Make your changes.
4. Test with MCP-compatible clients.

Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.

You can launch the MCP Inspector via npm with this command:

npx @modelcontextprotocol/inspector uv --directory /Users/wallison/TechProjects/mcp-server run url-text-fetcher

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.

📄 License

MIT License - see LICENSE file for details.