# ⚡ Figma MCP Bridge **Let an AI agent design in Figma — and actually see what it drew.** A zero-dependency MCP server that gives coding agents read *and write* access to a live Figma canvas, then closes the loop by handing the rendered PNG back to the model for visual self-critique. [![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE) [![MCP](https://img.shields.io/badge/MCP-JSON--RPC%202.0-8b5cf6.svg)](https://modelcontextprotocol.io/) [![Node.js](https://img.shields.io/badge/Node.js-18%2B-green.svg)](https://nodejs.org) [![Dependencies](https://img.shields.io/badge/npm%20dependencies-0-brightgreen.svg)](#engineering-notes) [![Tools](https://img.shields.io/badge/MCP%20tools-23-6366f1.svg)](#tool-reference) [![Works on](https://img.shields.io/badge/Figma%20plan-Free%20included-F24E1E.svg)](#how-its-different)

--- ![Figma MCP Bridge Demo](assets/demo.gif) *Agent generates the design, visually audits the rendered output, detects layout defects, and self-corrects in real time — zero human in the loop.* --- ## The problem Coding agents are effectively blind inside Figma. Most Figma MCP servers are **read-only** — they flatten a design into text so a model can turn it into code, and the traffic stops there. The ones that *can* write are either gated behind a paid Figma seat with a monthly tool-call quota, or expose a fixed vocabulary of commands (`create_rectangle`, `set_fill`) that runs out the moment the task gets specific. And none of them answer the question that actually matters after a write: **did it look right?** An agent that draws a card, gets back `{"ok": true}`, and moves on has no way to notice that its text overflowed, its contrast failed, or its frame landed on top of someone else's work. This bridge closes that loop, and adds the safety rails an autonomous agent needs to be trusted with a real design file. --- ## How it's different | | **This bridge** | [Figma Dev Mode MCP](https://help.figma.com/hc/en-us/articles/32132100833559-Guide-to-the-Figma-MCP-server) (official) | [Framelink](https://github.com/GLips/Figma-Context-MCP) | [Talk to Figma](https://github.com/sonnylazuardi/cursor-talk-to-figma-mcp) | |---|:---:|:---:|:---:|:---:| | **Writes to the canvas** | ✅ arbitrary JS in the sandbox | ✅ code-to-canvas | ❌ read-only | ✅ fixed command set | | **Visual feedback loop** | ✅ auto-framed PNG on every write | ⚠️ separate screenshot call | ❌ | ❌ | | **Undo the agent's work** | ✅ `figma_rollback` | ❌ | n/a | ❌ | | **Works on the Figma Free plan** | ✅ | ❌ Dev/Full seat, paid plan[¹](#sources) | ✅ | ✅ | | **Tool-call quota** | none — it's local | 6 / month on Starter seats[¹](#sources) | inherits REST rate limits | none | | **Token-optimized read of the *live* doc** | ✅ 86–91% smaller[²](#sources) | ⚠️ partial | ❌ REST only | ❌ | | **Persistent code modules in-sandbox** | ✅ `bridge.define/require` | ❌ | ❌ | ❌ | | **Long jobs survive their own timeout** | ✅ async `job_id` + progress | ❌ | n/a | ❌ | | **Install footprint** | 0 npm deps, `npx` *or* `git clone`, Node only | Figma desktop + paid seat | `npx` + access token | Bun + a second server process | **The short version:** Framelink is the best choice if you only want to turn an existing design into code. The official server is the safest choice if you're already on a paid Figma plan and want Code Connect. **This bridge is for the case where the agent is doing the designing** — where it needs to write freely, check its own work, and be undoable when it gets it wrong. --- ## How it works ```mermaid flowchart LR subgraph AI ["🤖 Coding Agent"] LLM["Claude Code · Cursor
Antigravity · Windsurf"] end subgraph Bridge ["⚡ MCP Server — Node.js, 0 deps"] Router["Tool Router
+ Job Ledger
+ Target Router"] Opt["Token Optimizer
REST + LIVE"] end subgraph Figma ["🎨 Figma Desktop"] Plugin["Bridge Plugin
Checkpoint Journal
Component Index"] Canvas["Live Canvas"] end LLM -->|"stdio JSON-RPC"| Router Router <-->|"WebSocket :8765"| Plugin Plugin -->|"execute in sandbox"| Canvas Canvas -->|"export PNG"| Plugin Plugin -->|"raw node tree"| Opt Opt -.->|"86% smaller"| LLM Plugin ==>|"screenshot + warnings"| LLM ``` The agent speaks plain MCP over stdio. The server owns a hand-rolled RFC 6455 WebSocket on `:8765`, which the Figma plugin connects to — so commands reach the canvas with no polling latency, and results (including multi-megabyte base64 PNGs) stream straight back. --- ## Quickstart ```bash npx @kolganovr/figma-mcp-bridge ``` Or, to read the installer before it touches your machine — it's the same script either way, just fetched differently: ```bash git clone https://github.com/kolganovr/figma-mcp-bridge.git cd figma-mcp-bridge node install.mjs ``` Both copy the server and plugin into place and register the MCP server in every AI client config they find — Claude Desktop, Claude Code, Cursor, Windsurf, Antigravity. The npm package exists purely for a shorter first command; it doesn't add a single runtime dependency — `dependencies` is empty in its `package.json` too, and no Python is needed either. `node` is the only runtime this project ever needs, for the installer and the server alike. Then, in **Figma Desktop**: 1. **Plugins → Development → Import plugin from manifest…** → pick `figma-plugin/manifest.json` 2. Press **`Ctrl + Alt + P`** (macOS: `Cmd + Option + P`) to launch **Antigravity Bridge** 3. Status turns green — **`CONNECTED`** Restart your AI client so it picks up the new tools. Verify anytime with: ```bash npx @kolganovr/figma-mcp-bridge --doctor # or: node install.mjs --doctor ```

Optional: Figma Cloud REST access

The live canvas tools need no token. If you also want to read *unopened* cloud files (`get_file`, `get_node`, `get_styles`, …), supply a personal access token: ```bash npx @kolganovr/figma-mcp-bridge --token "your_figma_personal_access_token" # or: node install.mjs --token "your_figma_personal_access_token" ``` Without a token these 7 tools aren't registered at all — see [Tool reference](#tool-reference).

--- ## What it gives the agent ### 1. Write freely, then look at the result `capture: true` returns a PNG of **exactly what the call just created or modified** — auto-framed to the changed nodes, never the whole page, and *never* by hijacking the user's selection. ```jsonc // agent calls figma_execute_code { "code": "const f = figma.createFrame(); /* ... */ return f.id;", "capture": true } // agent gets back — text + image in one response { "ok": true, "created": ["12:34"], "warnings": ["Text \"Total\" has ~3.1:1 contrast against its parent fill (WCAG AA wants 4.5:1)."], "checkpoint_id": "cp_mfk3p2a_7", "duration_ms": 840 } ``` The `warnings` array is a cheap auto-lint over the touched subtree — text overflow, low contrast, zero-size nodes. It catches the obvious mistakes **without spending a screenshot round trip**. ### 2. Undo anything the agent did Every write opens a checkpoint automatically. One call reverses it — no `Ctrl+Z` rolling back over the human's own unrelated work. ```jsonc // agent calls figma_rollback { "checkpoint_id": "last" } // gets back { "ok": true, "checkpoint_id": "cp_mfk3p2a_7", "label": "Generate checkout flow", "removed": ["12:34", "12:35"], // nodes the call created — deleted "restored": ["9:11"], // nodes it modified — properties put back "missing": [] // ids that no longer exist } ``` Created nodes are tracked automatically via a `Proxy` around `figma.create*()`. Property edits are tracked when snapshotted. Deletions are honestly reported as unrecoverable rather than silently lost. ### 3. Read the live canvas for ~700 tokens instead of ~5,000 The same pruning + Pseudo-JSX pipeline that powers the cloud tools, pointed at whatever is open right now. Measured on a realistic 6-card layout: **20 KB of raw API JSON → 2.7 KB (86% smaller)**. ```jsx Feature 0 ``` `budget_tokens` caps the response: if the requested depth overshoots, the server re-serializes the already-fetched tree shallower — no second round trip — and appends a comment saying what it did and which id to fetch for more. ### 4. Teach the sandbox new tricks that survive restarts Every `figma_execute_code` call is a fresh function scope, so helpers normally die instantly. `bridge.define` compiles and stores a module *inside the `.fig` document*: ```js // once bridge.define("kit", ` async function label(parent, text) { /* ... */ } module.exports = { label }; `); // in any later call — including next week, after a Figma restart const { label } = bridge.require("kit"); ``` ### 5. Long jobs that don't die at the timeout A generation still running after 30s hands back a `job_id` instead of failing while the plugin keeps working. Poll `figma_job_status` for live progress — the sandbox reports it via `progress(step, of, note)`. --- ## Tool reference Tools are served in **tiers**, so the schema list sent to the model on every turn stays proportional to what's actually usable: | Tier | Count | Registered when | |---|:---:|---| | **Core** | 8 | always | | **Extended** | 5 | always | | **REST** | 7 | only with `FIGMA_PERSONAL_ACCESS_TOKEN` set | | **Legacy** | 3 | only with `FIGMA_MCP_LEGACY_TOOLS=1` | Without a REST token an agent sees **13 tools instead of 23** — and never wastes a call on something that would only return `REST_TOKEN_MISSING`.

All 23 tools

--- ## Engineering notes The parts that were harder than they look — and why the code is shaped the way it is.

`eval` is a trap in the Figma sandbox

The obvious way to persist helpers between calls is "stash the source, `eval` it next time." It fails **silently**: `eval` is a *bound* function in Figma's sandbox, which by spec makes every call an **indirect eval** — declarations inside it reach neither the caller's scope nor `globalThis`. Nothing is defined, nothing throws. `bridge.define` is built on `new Function` instead, whose bodies are ordinary function scopes. The runtime's `bridge.info()` reports this contract to the agent on request, so it can ask instead of guessing.

A hand-rolled RFC 6455 WebSocket, on purpose

Zero npm dependencies isn't a vanity metric here — it means `git clone && node install.mjs` works on a locked-down machine with no registry access, and there's no supply chain to audit for something that executes arbitrary JS inside your design files. The cost is owning the framing: masking, fragmented continuation frames (a 4 MB screenshot arrives split, and treating each fragment as a whole message silently dropped it until the tool call timed out 40s later), ping/pong liveness, and a 64 MB ceiling so one frame can't exhaust memory.

Chunking `pluginData` by UTF-8 bytes, not string length

Figma caps `pluginData` entries at roughly 100 KB — measured in **bytes**. The original chunker sliced by JS string length, so a module written in Cyrillic (~2 bytes/char) produced "60,000-char" chunks that were really 120 KB, and `setPluginData` threw. The splitter now walks the real UTF-8 budget and never tears a surrogate pair.

Port ownership has to be reclaimable

Every agent spawns its own copy of the server; the first to bind `:8765` owns the plugin socket and the rest proxy to it. When the owner exits, a proxy has to be able to take over — otherwise every surviving agent stays permanently broken until restarted. A 5-second watchdog retries the bind, and a failed proxy call triggers an immediate takeover attempt.

Making placement O(neighbours) instead of O(n)

The original collision engine rescanned every top-level node for each of up to 200 candidate positions, then did it again in a second function in the same tick — and only ever stepped along one axis, so 20 generated screens became a mile-long ribbon nobody could zoom out to see. Bounds are now computed once and shared; collisions go through a 500px grid hash; and `layout:"grid"` shelf-packs into a compact rectangle.

Errors that tell the agent what to do instead

Raw Plugin API errors are famously unhelpful. Failures are matched against known modes and rewritten with a `HINT:` line naming the API that actually works, plus a stable machine-readable `code` (`FONT_NOT_LOADED`, `INSTANCE_TRANSFORM_LOCKED`, `STALE_NODE_ID`, `AUTOLAYOUT_HUG_RESIZE`, `AMBIGUOUS_TARGET`, …) so agents and tooling can branch on the failure type without parsing prose.

Security: this endpoint runs arbitrary JS in your design file

`:8765` is loopback, but loopback is reachable by **any web page the user happens to have open**. Two independent gates: an Origin allowlist (a browser cannot forge `Origin`, so a page on `evil.com` is rejected at the handshake) and a shared token that `install.mjs` generates and bakes into both the MCP config and the installed plugin — which also covers the sandboxed-iframe case, where a hostile page can present `Origin: "null"` too. Running straight from a clone with no token, the Origin gate still applies and the server prints a warning, so it degrades rather than silently opening up.

The one network call this server makes on its own: an update check

On startup the server compares the commit it was installed from (recorded by `install.mjs` into a `version.json` beside the copied code) against the latest commit on `main` via one GitHub API request, and prints a one-line notice to stderr if they differ. It never applies anything itself — `node install.mjs --update` is still a manual, deliberate step. This is the one thing in this project that assumes network access, so it's built to disappear cleanly when there isn't any: the check is fired without being awaited (never delays `initialize` or the first tool call), a failed/slow/offline request is caught and silently skipped, and results are cached for 24h so it doesn't hit GitHub's unauthenticated rate limit or run once per spawned copy of the server. Set `FIGMA_MCP_NO_UPDATE_CHECK=1` to turn it off entirely — worth doing on the locked-down machines the previous note is about.

--- ## Testing Five dependency-free suites, all runnable with bare `node`: ```bash node tests/bridge-runtime.test.js # sandbox runtime, module persistence, checkpoint/rollback node tests/layout-packer.test.js # row/grid packing, collision grid node tests/optimizer.test.js # jsx/tree/json serialization, budget truncation node tests/mcp-protocol.test.js # real server over stdio: initialize, tools/list, tiering node tests/install.test.js # config merge/reuse, token persistence, stale-file cleanup ``` `mcp-protocol.test.js` spawns the actual server as a child process and speaks NDJSON to it — the same transport a real MCP client uses — rather than importing internals. --- ## Repository layout ``` figma-mcp-bridge/ ├── figma/ # MCP server (Node.js, stdio + WebSocket) │ ├── index.js # protocol, tool router, job ledger, target router │ ├── optimizer/ # AST pruner, style collapser, JSX/tree serializers │ ├── instructions.md # agent-facing protocol docs (served on `initialize`) │ └── *.json # per-tool schemas ├── figma-plugin/ # Figma Desktop plugin │ ├── code.js # sandbox executor, bridge runtime, checkpoints, capture │ └── ui.html # HUD — stream, settings, control (pause / undo) ├── tests/ # 5 suites, 0 dependencies ├── install.mjs # cross-platform installer, updater, doctor (Node only) └── AGENTS.md # onboarding protocol for AI agents ``` --- ## Sources 1. Seat and quota requirements for the official server — [Figma: Guide to the Figma MCP server](https://help.figma.com/hc/en-us/articles/32132100833559-Guide-to-the-Figma-MCP-server), [Figma Developer Docs: Rate limits & access](https://developers.figma.com/docs/figma-mcp-server/rate-limits-access/) 2. Token reduction measured on a 6-card layout fixture that mimics real REST output: 20,587 B raw → 2,862 B Pseudo-JSX (86.1%) / 1,912 B tree (90.7%). The fixture is checked in and asserted — run `node tests/optimizer.test.js` to reproduce the exact figures. Comparison reflects publicly documented behaviour as of August 2026. Alternatives are actively developed — verify current capabilities before making a decision on this table alone. --- ## License [MIT](LICENSE) · Built by **Roman Kolganov**