Markdown Web Crawl MCP server

This MCP web crawler project extracts and saves website content for use with the Model Context Protocol. It offers functionality to extract website content as markdown, map site structure, process multiple URLs in batches, and customize your output locations.

Installation

Prerequisites

• Python 3.7+
• FastMCP

Setup Steps

Clone the repository:

git clone https://github.com/yourusername/webcrawler.git
cd webcrawler

Install required dependencies:

pip install -r requirements.txt

Install FastMCP if you haven't already:

uv pip install fastmcp

Configuration

The crawler can be configured using environment variables:

• OUTPUT_PATH: Sets the default directory for saved files
• MAX_CONCURRENT_REQUESTS: Controls maximum parallel requests (default: 5)
• REQUEST_TIMEOUT: Sets request timeout in seconds (default: 30)

Example of setting the output directory:

export OUTPUT_PATH=./output

Running the Server

Using FastMCP

Install the server with FastMCP:

fastmcp install server.py

Using Custom Settings

You can run with custom settings by configuring FastMCP directly:

"Crawl Server": {
      "command": "fastmcp",
      "args": [
        "run",
        "/Users/mm22/Dev_Projekte/servers-main/src/Webcrawler/server.py"
      ],
      "env": {
        "OUTPUT_PATH": "/Users/user/Webcrawl"
      }
}

Usage Examples

Extracting Website Content

To extract and save content from a specific URL:

mcp call extract_content --url "https://example.com" --output_path "example.md"

Creating a Content Index

To scan a website and create an index of its content:

mcp call scan_linked_content --url "https://example.com" | \
  mcp call create_index --content_map - --output_path "index.md"

Output

All crawled content is automatically saved in markdown format within your specified output directory. If no directory is specified, it will use the default path set in your environment variables.

How to install this MCP server

For Claude Code

To add this MCP server to Claude Code, run this command in your terminal:

claude mcp add-json "Crawl-Server" '{"command":"fastmcp","args":["run","server.py"],"env":{"OUTPUT_PATH":"./output"}}'

See the official Claude Code MCP documentation for more details.

For Cursor

There are two ways to add an MCP server to Cursor. The most common way is to add the server globally in the ~/.cursor/mcp.json file so that it is available in all of your projects.

If you only need the server in a single project, you can add it to the project instead by creating or adding it to the .cursor/mcp.json file.

Adding an MCP server to Cursor globally

To add a global MCP server go to Cursor Settings > Tools & Integrations and click "New MCP Server".

When you click that button the ~/.cursor/mcp.json file will be opened and you can add your server like this:

{
    "mcpServers": {
        "Crawl Server": {
            "command": "fastmcp",
            "args": [
                "run",
                "server.py"
            ],
            "env": {
                "OUTPUT_PATH": "./output"
            }
        }
    }
}

Adding an MCP server to a project

To add an MCP server to a project you can create a new .cursor/mcp.json file or add it to the existing one. This will look exactly the same as the global MCP server example above.

How to use the MCP server

Once the server is installed, you might need to head back to Settings > MCP and click the refresh button.

The Cursor agent will then be able to see the available tools the added MCP server has available and will call them when it needs to.

You can also explicitly ask the agent to use the tool by mentioning the tool name and describing what the function does.

For Claude Desktop

To add this MCP server to Claude Desktop:

1. Find your configuration file:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json
• Linux: ~/.config/Claude/claude_desktop_config.json

2. Add this to your configuration file:

{
    "mcpServers": {
        "Crawl Server": {
            "command": "fastmcp",
            "args": [
                "run",
                "server.py"
            ],
            "env": {
                "OUTPUT_PATH": "./output"
            }
        }
    }
}

3. Restart Claude Desktop for the changes to take effect