figma-mcp

Integrations

  • Allows AI coding agents to access Figma files and prototypes directly, providing capabilities to retrieve components, specific nodes, and workflow connections from Figma designs using the Figma API.

Figma MCP Python

Allow your AI coding agents to access Figma files & prototypes directly. You can DM me for any issues / improvements: https://x.com/jasonzhou1993

Quick Installation with pipx

pipx install figma-mcp

For Cursor:

  1. In settings, add an MCP server using the command:
figma-mcp --figma-api-key=your_figma_key
  1. OR Add a .cursor/mcp.json file in your project:
{ "mcpServers": { "figma-python": { "command": "figma-mcp", "args": [ "--figma-api-key=your_figma_key" ] } } }

For other IDEs like Windsurf, use an MCP configuration file (e.g., mcp_config.json):

{ "mcpServers": { "figma-python": { "command": "figma-mcp", "args": [ "--figma-api-key=your_figma_key" ] } } }

Install uv and set up the environment

curl -LsSf https://astral.sh/uv/install.sh | sh uv venv source .venv/bin/activate uv sync

Test locally

python -m figma_mcp.main

You must be authenticated.

A
security – no known vulnerabilities
A
license - permissive license
A
quality - confirmed to work

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Allow your AI coding agents to access Figma files & prototypes directly. You can DM me for any issues / improvements: https://x.com/jasonzhou1993

  1. Access all figma pages
  2. Access all figma components
  3. Access figma prototype flows
  1. Quick Installation with pipx
    1. For Cursor:
    2. For other IDEs like Windsurf, use an MCP configuration file (e.g., mcp_config.json):
  2. Install uv and set up the environment
    1. Test locally

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