Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Description from the maker (original English)
Figma MCP: list frames in a file and fetch one frame's JSON and image safely. 2 tools.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
FIGMA_TOKEN, FIGMA_API_BASE_URL, FIGMA_REQUEST_TIMEOUT_MS, FIGMA_MAX_JSON_BYTES, FIGMA_MAX_FRAME_BYTES, FIGMA_OUTPUT_ROOT, FIGMA_ALLOW_HTTP_FOR_TESTSValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
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Pick your app above. We remember it, so next time the button says “Install in …”.
Download the maker’s .mcpb file
The link goes to the maker’s own file; we do not host or repackage it. Open the file and Claude Desktop installs it.
Run this in your terminal
claude mcp add figma --env FIGMA_TOKEN=your-value --env FIGMA_API_BASE_URL=your-value --env FIGMA_REQUEST_TIMEOUT_MS=your-value --env FIGMA_MAX_JSON_BYTES=your-value --env FIGMA_MAX_FRAME_BYTES=your-value --env FIGMA_OUTPUT_ROOT=your-value --env FIGMA_ALLOW_HTTP_FOR_TESTS=your-value -- npx -y @scalably-io/figma-mcpFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"figma": {
"command": "npx",
"args": [
"-y",
"@scalably-io/figma-mcp"
],
"env": {
"FIGMA_TOKEN": "your-value",
"FIGMA_API_BASE_URL": "your-value",
"FIGMA_REQUEST_TIMEOUT_MS": "your-value",
"FIGMA_MAX_JSON_BYTES": "your-value",
"FIGMA_MAX_FRAME_BYTES": "your-value",
"FIGMA_OUTPUT_ROOT": "your-value",
"FIGMA_ALLOW_HTTP_FOR_TESTS": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"figma": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@scalably-io/figma-mcp"
],
"env": {
"FIGMA_TOKEN": "your-value",
"FIGMA_API_BASE_URL": "your-value",
"FIGMA_REQUEST_TIMEOUT_MS": "your-value",
"FIGMA_MAX_JSON_BYTES": "your-value",
"FIGMA_MAX_FRAME_BYTES": "your-value",
"FIGMA_OUTPUT_ROOT": "your-value",
"FIGMA_ALLOW_HTTP_FOR_TESTS": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
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FIGMA_API_BASE_URL envFIGMA_REQUEST_TIMEOUT_MS envFIGMA_MAX_JSON_BYTES envFIGMA_MAX_FRAME_BYTES envFIGMA_OUTPUT_ROOT envFIGMA_ALLOW_HTTP_FOR_TESTS envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified against the domain scalably.io (the registry checks domain ownership)
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
You need to fill in: FIGMA_TOKEN
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (1.0.1) reached the registry 2 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js, MCPB on your computer.
In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Let any LLM watch a video locally — and search everything it has ever watched.
Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
Figma REST API MCP server. 2 tools list the top-level frames in a file and fetch one frame's rendered PNG plus its node JSON and image-fill map into a local output directory.
Claude Code:
claude mcp add figma -e FIGMA_TOKEN=your-token -- npx -y @scalably-io/figma-mcp
Codex:
codex mcp add figma --env FIGMA_TOKEN=your-token -- npx -y @scalably-io/figma-mcp
Claude Desktop: download figma-mcp.mcpb from the latest GitHub release and open it.
file_content:read scope./design/ or /file/, for example https://www.figma.com/design/AbC123xyz/My-file gives AbC123xyz. Both tools take it as file_key.FIGMA_TOKEN is not set the server still starts and lists its tools; every call then fails with FIGMA_NOT_CONFIGURED until the token is provided.fetch_frame is the only tool that writes files (so it is not marked read-only); it writes frame.png, node.json, and fills.json into a directory below the configured output root (default ./figma-output). The other tool is fully read-only.| Tool | What it does |
|---|---|
list_frames | List and optionally filter all top-level FRAME nodes in a Figma file, with exact page/name/node-id data, dimensions, and file metadata |
fetch_frame | Fetch one Figma frame and transactionally write frame.png, node.json, and a normalized image-fill map into a directory below the output root |
| Variable | Required | Purpose |
|---|---|---|
FIGMA_TOKEN | yes | Figma personal access token with file_content:read |
FIGMA_API_BASE_URL | no | Override the Figma REST API base URL (default https://api.figma.com/v1) |
FIGMA_REQUEST_TIMEOUT_MS | no | Per-request timeout in milliseconds (default 60000) |
FIGMA_MAX_JSON_BYTES | no | Upper bound on a Figma JSON response, in bytes (default 104857600) |
FIGMA_MAX_FRAME_BYTES | no | Upper bound on a downloaded frame PNG, in bytes (default 104857600) |
FIGMA_OUTPUT_ROOT | no | Directory that every fetch_frame output directory must stay below (default ./figma-output, created on first use) |
FIGMA_ALLOW_HTTP_FOR_TESTS | no | Test suite only: 1 allows a plain-HTTP loopback API base. Never set it in normal use |
Every tool returns plain JSON with status (succeeded, partial, no_op), summary, target, result, proof, warnings, recovery. Failures throw a plain error string: : .
fetch_frame renders through Figma's image API, so very large frames or extreme scale values can exceed the configured JSON or frame byte limits; lower scale or split the frame if that happens. fills.json URLs are temporary and expire within 14 days.
Each release lists the package version, the .mcpb sha256 and the production commit it was derived from in CHANGELOG.md. CI runs the tests and a clean install of the packed tarball on every push.
This server runs locally, on your machine, under your own credentials. It collects no personal data, contains no telemetry, stores nothing persistently beyond the frame bundles you explicitly fetch, and talks only to the vendor API it wraps. No third party, including Scalably, receives your data. Contact: hello@scalably.io. Canonical copy: https://scalably.io/connector-privacy.html
MIT. Copyright Scalably.