Cursor 🤝 FastMCP

Cursor supports MCP servers through multiple transport methods including STDIO, SSE, and Streamable HTTP, allowing you to extend Cursor’s AI assistant with custom tools, resources, and prompts from your FastMCP servers.

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Requirements

This integration uses STDIO transport to run your FastMCP server locally. For remote deployments, you can run your FastMCP server with HTTP or SSE transport and configure it directly in Cursor’s settings.

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Create a Server

The examples in this guide will use the following simple dice-rolling server, saved as server.py.

import random
from fastmcp import FastMCP

mcp = FastMCP(name="Dice Roller")

@mcp.tool
def roll_dice(n_dice: int) -> list[int]:
    """Roll `n_dice` 6-sided dice and return the results."""
    return [random.randint(1, 6) for _ in range(n_dice)]

if __name__ == "__main__":
    mcp.run()

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Install the Server

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FastMCP CLI

The easiest way to install a FastMCP server in Cursor is using the fastmcp install cursor command. This automatically handles the configuration, dependency management, and opens Cursor with a deeplink to install the server.

fastmcp install cursor server.py

The install command supports the same file.py:object notation as the run command. If no object is specified, it will automatically look for a FastMCP server object named mcp, server, or app in your file:

# These are equivalent if your server object is named 'mcp'
fastmcp install cursor server.py
fastmcp install cursor server.py:mcp

# Use explicit object name if your server has a different name
fastmcp install cursor server.py:my_custom_server

After running the command, Cursor will open automatically and prompt you to install the server. The command will be uv, which is expected as this is a Python STDIO server. Click “Install” to confirm:

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Dependencies

If your server has dependencies, include them with the --with flag:

fastmcp install cursor server.py --with pandas --with requests

Alternatively, you can specify dependencies directly in your server code:

from fastmcp import FastMCP

mcp = FastMCP(
    name="Dice Roller",
    dependencies=["pandas", "requests"]
)

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Environment Variables

If your server needs environment variables (like API keys), you must include them:

fastmcp install cursor server.py --name "Weather Server" \
  --env-var API_KEY=your-api-key \
  --env-var DEBUG=true

Or load them from a .env file:

fastmcp install cursor server.py --name "Weather Server" --env-file .env

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Generate MCP JSON

You can generate MCP JSON configuration for manual use:

# Generate configuration and output to stdout
fastmcp install mcp-json server.py --name "Dice Roller" --with pandas

# Copy configuration to clipboard for easy pasting
fastmcp install mcp-json server.py --name "Dice Roller" --copy

This generates the standard mcpServers configuration format that can be used with any MCP-compatible client.

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Manual Configuration

For more control over the configuration, you can manually edit Cursor’s configuration file. The configuration file is located at:

• All platforms: ~/.cursor/mcp.json

The configuration file is a JSON object with a mcpServers key, which contains the configuration for each MCP server.

{
  "mcpServers": {
    "dice-roller": {
      "command": "python",
      "args": ["path/to/your/server.py"]
    }
  }
}

After updating the configuration file, your server should be available in Cursor.

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Dependencies

If your server has dependencies, you can use uv or another package manager to set up the environment.

{
  "mcpServers": {
    "dice-roller": {
      "command": "uv",
      "args": [
        "run",
        "--with", "pandas",
        "--with", "requests", 
        "python",
        "path/to/your/server.py"
      ]
    }
  }
}

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Environment Variables

You can also specify environment variables in the configuration:

{
  "mcpServers": {
    "weather-server": {
      "command": "python",
      "args": ["path/to/weather_server.py"],
      "env": {
        "API_KEY": "your-api-key",
        "DEBUG": "true"
      }
    }
  }
}

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Using the Server

Once your server is installed, you can start using your FastMCP server with Cursor’s AI assistant.

Try asking Cursor something like:

“Roll some dice for me”

Cursor will automatically detect your roll_dice tool and use it to fulfill your request, returning something like:

🎲 Here are your dice rolls: 4, 6, 4

You rolled 3 dice with a total of 14! The 6 was a nice high roll there!

The AI assistant can now access all the tools, resources, and prompts you’ve defined in your FastMCP server.