Figma API

MCP Server generated by mcp.ag2.ai

python

1

GitHub Stars

python

Language

4 months ago

First Indexed

3 weeks ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "huazhengwang-figma-api": {
      "command": "python",
      "args": [
        "mcp_server/main.py",
        "stdio"
      ],
      "env": {
        "CONFIG": "JSON string containing the configuration",
        "SECURITY": "Environment variables for security parameters (e.g., API keys)",
        "CONFIG_PATH": "Path to a JSON configuration file (e.g., mcp_server/mcp_config.json)"
      }
    }
  }
}

This MCP server lets you run a multi-agent conversation platform for the Figma OpenAPI-based API, enabling coordinated interactions between agents through a configurable runtime. You can start the server locally in stdio mode and connect clients or agents to drive conversations against the API surface in a controlled, testable environment.

How to use

You will start the MCP server in stdio mode and then connect your MCP clients to it. Use a client that can communicate via the MCP protocol over a stdio-based session. Start the server with the provided runtime command, then supply configuration through environment variables or a JSON config file.

How to install

Prerequisites: Python 3.9 or newer, and the uv tool.

Clone the project to your local machine.

Install development dependencies with pip in editable mode.

pip install -e ".[dev]"

Alternatively, install dependencies using uv.

uv pip install --editable ".[dev]"

Start the MCP server in stdio mode using Python.

python mcp_server/main.py stdio

Configuration and runtime notes

Configure how the server loads its settings via environment variables.

You can provide a JSON configuration object directly through an environment variable or a file path.

Security and environment variables

Use the following environment variables to control security and configuration.

Starting parameters and environment variables

The server can be started with the standard runtime command shown above. You can configure the runtime with these environment variables.

Development and testing tips

For development, you can run linting, static analysis, and tests to ensure code quality and stability.

Notes

The following sections provide recommended local development workflows and practical usage tips for MCP clients when interacting with this server.

Available tools

Linting and formatting

Check code quality with ruff and format code with ruff format to maintain consistency.

Static analysis

Run static analysis tools (mypy, bandit, semgrep) to catch type and security issues.

Testing

Execute tests with pytest and generate coverage reports.

Pre-commit hooks

Install and run pre-commit hooks to enforce code standards before commits.