Fetch MCP server

The Fetch MCP Server provides web content fetching capabilities for Large Language Models (LLMs). It enables models to retrieve and process web page content by converting HTML to markdown for easier consumption. The server can deliver content in chunks, allowing models to read webpages incrementally until they find the needed information.

Installation Options

Using uv (Recommended)

When using uv, no specific installation is needed. You can use uvx to directly run the server:

# No installation required when using uvx

Using PIP

Alternatively, install via pip:

pip install mcp-server-fetch

After installation, run it as a script:

python -m mcp_server_fetch

Optional: Node.js

Installing Node.js is optional but recommended for a more robust HTML simplifier:

# Install Node.js using your system's package manager
# Example for Ubuntu/Debian:
apt-get install nodejs

Configuration

Configure for Claude.app

Add to your Claude settings based on your installation method:

For uvx:

"mcpServers": {
  "fetch": {
    "command": "uvx",
    "args": ["mcp-server-fetch"]
  }
}

For docker:

"mcpServers": {
  "fetch": {
    "command": "docker",
    "args": ["run", "-i", "--rm", "mcp/fetch"]
  }
}

For pip installation:

"mcpServers": {
  "fetch": {
    "command": "python",
    "args": ["-m", "mcp_server_fetch"]
  }
}

Customization Options

Robots.txt Behavior

By default, the server respects robots.txt for model-initiated requests but not for user-initiated requests. To disable this behavior:

"args": ["mcp-server-fetch", "--ignore-robots-txt"]

User-Agent Configuration

Default user-agents are:

• For model requests: ModelContextProtocol/1.0 (Autonomous; +https://github.com/modelcontextprotocol/servers)
• For user requests: ModelContextProtocol/1.0 (User-Specified; +https://github.com/modelcontextprotocol/servers)

To customize:

"args": ["mcp-server-fetch", "--user-agent=YourUserAgent"]

Using the Fetch Tool

The server provides a fetch tool with the following parameters:

• url (string, required): URL to fetch
• max_length (integer, optional): Maximum characters to return (default: 5000)
• start_index (integer, optional): Start content from this character index (default: 0)
• raw (boolean, optional): Get raw content without markdown conversion (default: false)

Example Usage:

# Basic fetch request
fetch(url="https://example.com")

# Fetch with parameters
fetch(url="https://example.com", max_length=10000, start_index=500, raw=false)

Debugging

Use the MCP inspector to debug the server:

# For uvx installations
npx @modelcontextprotocol/inspector uvx mcp-server-fetch

# For specific directory installations
cd path/to/servers/src/fetch
npx @modelcontextprotocol/inspector uv run mcp-server-fetch

How to add this MCP server to 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 > MCP and click "Add new global MCP server".

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

{
    "mcpServers": {
        "cursor-rules-mcp": {
            "command": "npx",
            "args": [
                "-y",
                "cursor-rules-mcp"
            ]
        }
    }
}

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 explictly ask the agent to use the tool by mentioning the tool name and describing what the function does.