Figma MCP Server

The MCP Figma server bridges the gap between AI assistants and the rich ecosystem of Figma’s design platform. By exposing every public endpoint of the Figma REST API as a Model Context Protocol (MCP) tool, it allows Claude or other AI clients to query and manipulate design files, projects, teams, comments, components, styles, webhooks, and library analytics without leaving the conversational interface. This removes the friction of manual API calls or SDK usage, enabling designers and developers to ask high‑level questions—such as “Show me all components used in the latest sprint” or “Post a comment on this frame”—and receive structured responses directly within their AI workflow.

For developers, the server’s value lies in its full coverage of Figma functionality. It supports user authentication (), file retrieval with adjustable depth for large files, node extraction, image rendering, and version history. Comment management tools let AI agents add or delete comments and reactions, fostering real‑time collaboration. Team and project listings (, ) help organize assets, while component and style tools provide granular access to reusable elements. The inclusion of webhook management (V2 API) enables automated triggers for design changes, and library analytics tools expose usage metrics that can inform design system health.

Key capabilities are delivered through a consistent, declarative tool set. Each operation follows the same naming convention () and accepts JSON parameters, making it easy for AI assistants to generate calls from natural language prompts. The server also handles pagination and depth control, ensuring that large files can be fetched efficiently by first retrieving a shallow structure () and then expanding only when deeper details are required. This design reduces latency and bandwidth consumption during interactive sessions.

Real‑world scenarios benefit from this tight integration. A product manager can ask the AI to pull the latest design version, extract all component usage statistics, and automatically post a comment summarizing findings. A front‑end engineer might request the exact image URL for a component to embed in documentation, or have the AI generate a webhook that notifies the CI pipeline when a file changes. Designers can quickly inspect comment reactions or delete outdated comments, all without switching tools.

Because MCP servers are stateless and composable, the Figma server can be combined with other domain‑specific MCPs—such as a code generation or documentation server—to create end‑to‑end design‑to‑code pipelines. The unique advantage of this implementation is its comprehensive coverage: every publicly documented Figma endpoint is available, and the server handles authentication and rate‑limiting transparently. This makes it a powerful asset for any team that wants to embed design intelligence directly into AI‑driven workflows.