Figma MCP Integration

Weldable's Figma MCP integration gives your AI agents access to Figma's design platform for reading file data, extracting component information, and managing comments through natural language. Figma has been expanding its AI capabilities with features like Figma Make and built-in generative tools powered by Gemini and GPT. Weldable connects Figma to your broader workflow so your agents can bridge the gap between design and engineering tooling.

Your agent handles requests in plain English. Ask it to pull component details from a design file, read comments on a prototype, or extract color tokens, and Weldable maps the intent to the right Figma API call.

Use cases

Design-to-development handoff

Your agent reads a Figma file and extracts component names, dimensions, colors, and typography values. It formats this information as a structured specification and posts it to a Linear or Jira issue, giving engineers the exact values they need without switching between Figma and their project management tool. This replaces the manual process of screenshotting design specs and pasting them into tickets.

Design review tracking

Your agent queries all comments on a Figma file and groups them by status: resolved, unresolved, and new since the last review. It generates a summary and posts it to Slack so the design team knows what feedback still needs attention. For teams that run async design reviews, this turns scattered Figma comments into an actionable checklist.

Component inventory audits

Your agent reads the components and styles defined in a Figma design system file. It compares the component list against a reference in Google Sheets to identify components that exist in the design system but have not been implemented in code, or vice versa. This keeps design and engineering aligned on what the system includes without manual cross-referencing.

Brand consistency checks

When a new design file is created, your agent reads the colors and fonts used across all frames. It compares them against the approved brand token values stored in your design system file and flags any deviations. The report goes to the design lead in Slack with the specific frames and values that are off-brand. This catches inconsistencies early, before they reach production.

Stakeholder feedback collection

Your agent posts a comment on a Figma prototype linking to a feedback form, then monitors the file for new comments from stakeholders. It collects all feedback, groups it by frame, and creates Linear issues for actionable items. Designers get organized feedback without manually reading through dozens of scattered comments.

How it works

Connect your Figma account through OAuth. Weldable requests read access to your files and the ability to manage comments. Tokens refresh automatically so your agent maintains access without manual re-authentication.

Describe what you need in natural language. Weldable resolves file keys, node IDs, and comment threads behind the scenes. Your agent can chain Figma data with other integrations: extract design tokens from Figma, format them, and create a pull request in GitHub with updated CSS variables.

Tips

Figma file keys are in the URL. When referencing a specific file, you can share the Figma URL and Weldable extracts the file key automatically. No need to manually parse the URL or look up file identifiers in the API.

Node IDs target specific frames or components. If you only need data from one section of a large file, specify the frame name and your agent will resolve it to the correct node ID. This avoids pulling the entire file tree when you only need a subset.

Comments are tied to specific coordinates. When your agent posts a comment, it can pin it to a specific frame or region in the design. This makes feedback contextual rather than floating at the file level.

Design tokens come from styles and variables. Figma's variables and styles API exposes color, typography, and spacing tokens. Your agent can extract these programmatically, which is useful for keeping design tokens in sync with code without manual export steps.

Large files return a lot of data. Figma files with hundreds of frames produce substantial API responses. Scope your queries to specific pages or components when possible. This keeps response times fast and reduces the amount of data your agent needs to process.