cursor-talk-to-figma-mcp
TalkToFigma: MCP integration between AI Agent (Cursor, Claude Code, Codex) and Figma, allowing Agentic AI to communicate with Figma for reading designs and modifying them programmatically.
Runs with mockssource: GitHubhomepageJavaScriptMITcommit ddd90f3a6d45
JavaScript, MIT licensed. The project labels itself: agent, agentic, agentic ai, ai, ai agents, automation, claude code and codex.
cursor-talk-to-figma-mcp runs, with stand-ins for the services it depends on. An Argusic agent installed it in 6 minutes and hit no errors on a clean machine with no GPU, and the whole session was recorded.
Dependencies installed, the project builds with tsup, the WebSocket relay starts on port 3055, and the MCP server starts on stdio, initializes, connects to the relay, and responds to all MCP protocol messages (initialize, tools/list, prompts/list, tools/call).
What the agent ended up with on a clean machine, in its own words. How this is measured
Measured by Argusic on a fresh machine every time. Every number links to its evidence. Argusic Score 56 of 100 (the mean of this project's run scores).
At a glance
Subject data from GitHub, linked at the top of this page, refreshed . Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.
What was measured
From the run that decided this verdict. Every line is a recorded value, not an estimate.
- Install time
- 6 minutes
- Cold machine to finish
- 8 minutes
- Errors hit and fixed
- 0 hit, 0 fixed with no human help
- Model tokens used
- 80,026
- Exact commit tested
- ddd90f3a6d45
- Container image
- sha256:4c3d41857be3
What was not measured
The other half, so you can see exactly how far this evidence goes. A gap is printed as a gap and never filled in.
- How the result was proved
- runs before 2026-09-07 did not record the command used to check the result
- Peak GPU memory
- this ran on a CPU machine, so there was no GPU to sample
- Behaviour over a long run
- each attempt uses the smallest documented settings and a fixed time budget, so this measures whether it runs, not how it holds up under load
- Behaviour against real services
- this run was verified against stand-in services only
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
succeeded in 0ms: total 484 drwxr-xr-x 2 runner runner 4096 Sep 3 16:21 . drwxr-xr-x 8 runner runner 4096 Sep 3 16:21 .. -rwxr-xr-x 1 runner runner 86667 Sep 3 16:21 server.cjs -rw-rw-r-- 1 runner runner 149880 Sep 3 16:21 server.cjs.map -rw-rw-r-- 1 runner runner 20 Sep 3 16:21 server.d.cts -rw-rw-r-- 1 runner runner 20 Sep 3 16:21 server.d.ts -rwxr-xr-x 1 runner runner 83592 Sep 3 16:21 server.js -rw-rw-r-- 1 runner runner 149835 Sep 3 16:21 server.js.map tokens used 80,026
Replay the whole session, every command from a clean machine to this point.
How it was tested
One agent, one container, no human help. It installs the project the way its own documentation says to, runs it, and fixes what breaks. Everything below is recorded as it happened: the terminal session, the log and the exact commit. The full method.
Strengths and limits
Measured facts, not opinions. How this is written.
What went well
- Installed in 6 minutes, faster than the median of the 32 comparable projects Argusic has measured.
- Nothing broke on the way: zero errors between clone and running.
- Licensed MIT, as reported by its host.
- Measured 2 times, so the result is not a one-off.
What did not, or is not known
- Only reached a running state against stand-in services, so nothing here proves it works against the real ones.
Of the 33 agent projects Argusic has installed and timed, cursor-talk-to-figma-mcp was the 17th fastest to reach a running state, and 25 of 33 reached one at all.
Also tested, in the same area
Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.
Run history
| tested by | attempt | outcome | score | cost USD | when |
|---|---|---|---|---|---|
| Argusic Runner | 2/3 | Did not run | 20.00 | 0.13 | |
| Argusic Runner | 1/3 | Runs with mocks | 92.00 | 0.03 |
Topics (from GitHub)
agentagenticagentic-aiaiai-agentsautomationclaude-codecodexcursordesignfigmagenerative-aillmllmsmcpmodel-context-protocol
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/cursor-talk-to-figma-mcp)Questions
- Does cursor-talk-to-figma-mcp run?
- cursor-talk-to-figma-mcp runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 6 minutes, hitting 0 errors on the way, and recorded the session.
- How did Argusic test cursor-talk-to-figma-mcp?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit ddd90f3a6d45. 2 attempts are recorded, and the full method is on the methodology page.
- What did it cost to test cursor-talk-to-figma-mcp?
- The run that produced this verdict cost $0.03: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does cursor-talk-to-figma-mcp take to install?
- 6 minutes in the run that decided this verdict, from a clean machine to a running state. That is one measured attempt, not an average.
- Does cursor-talk-to-figma-mcp need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing cursor-talk-to-figma-mcp?
- Nothing did, in the recorded run: zero errors between clone and running.
- How does cursor-talk-to-figma-mcp compare with the alternatives?
- Of the 33 agent projects Argusic has installed and timed, cursor-talk-to-figma-mcp was the 17th fastest to reach a running state, and 25 of 33 reached one at all.
- Where is the evidence for cursor-talk-to-figma-mcp?
- All 2 recorded runs are on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.