Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Beschreibung vom Entwickler (englisches Original)
Parametric CAD as code: model 3D-printable parts on an exact B-rep kernel, measured.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Die .mcpb-Datei des Entwicklers herunterladen
Der Link führt zur Datei des Entwicklers selbst; wir hosten sie nicht und verpacken sie nicht neu. Öffne die Datei, dann installiert Claude Desktop sie.
Führe das in deinem Terminal aus
Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto ierehon1905 bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.0.14) kam gestern in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du MCPB auf deinem Computer.
In derselben Kategorie: Figma Context MCP, Claude Real Video, Figma MCP Server
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
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.
The Figma MCP server brings Figma design context directly into your AI workflow.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
Parametric CAD you write as code — for people, and for agents.
Status: 0.0.14, experimental. Made by Maging Studio, and the DSL still moves. Every operation is checked against measured geometry (eval/cases/), but none of it has had the years of abuse that make a CAD kernel trustworthy. Measure a part before you machine it.
Start here: Getting started, five minutes in a browser tab.
const plate = box(80, 60, 8).tag("plate");
const wall = box(8, 60, 40).at(-36, 0, 20).tag("wall");
const body = union(plate, wall, { blend: 6 }); // the blend is the fillet const drilled = body.cut(...grid(2, 2, 36, 40).map(([x, y]) => cylinder(3, 32).at(x, y)));
return drilled .edges({ curve: "circle", role: "hole", adjacentTo: { faceNormal: "+z" } }) .expect({ count: 4 }) // a build error, not a surprise .fillet(0.8);
You never name an edge by index. You describe it — *the circular rims that open onto the top face* — and the description still works after you move a hole.
Your script builds a small JSON graph, and an exact kernel reads it — OpenCASCADE: real faces and edges, STEP export, and a refusal rather than an approximation when it cannot do something faithfully. The graph is what keeps today's script working after tomorrow's kernel swap.
Every kernel returns valid-looking wrong answers somewhere, OpenCASCADE and NVIDIA's newly open SMLIB included. ParCAD carries five patches to OpenCASCADE 8.0.1 for the cases its parts ran into, and checks each build itself after the kernel reports success.
Parts get measured, not assumed — volume, wall thickness, whether two bores actually meet. An agent gets the same numbers over MCP, with no screen to look at.
And when it does look, it gets pictures made for reading: views that share one scale, sections through the inside, and every surface coloured by the tag that built it.
It is aimed at small mechanical parts — brackets, flanges, manifolds, heat sinks, the things you print or machine one of. examples/ has thirty-one.
Those are good, and much older. Three differences. Selectors are *descriptive and checked* — .expect({ count: 4 }) turns a selector that silently started matching three edges into a build error, which is the failure mode that makes code-CAD fragile. What you see, what you measure and what you export come off one exact B-rep, so the preview and the STEP file are one model, not two projects. And measurement is an output rather than something you eyeball, which is what makes the MCP surface real instead of a wrapper.
With Homebrew, on macOS or Linux (Linux from 0.0.6), which installs the host and no window:
brew tap ierehon1905/parcad
brew trust ierehon1905/parcad brew install parcad
Then add it to your agent, which starts parcad when it needs it. To use the app yourself, run parcad serve and open http://127.0.0.1:4242 — the whole app is there, in your browser.
Nothing on the Homebrew path is quarantined. The same parcad is the headless driver (parcad part.js), and a client of the running host: parcad tools lists what an agent can call over MCP and parcad call calls it from a shell.
Or the desktop app, from Releases:
| platform | download |
|---|---|
| macOS, Apple silicon | ParCAD-aarch64-apple-darwin.zip — unzip, drag to Applications |
| Linux x86_64 | .deb or .AppImage (also on AppImageHub) |
| Windows x86_64 | .msi or -setup.exe (a winget package is waiting for review) |
Each platform's build measures the whole eval corpus with the worker it ships before it is uploaded. The Mac app is not notarised yet, so macOS refuses it the first time: run xattr -dr com.apple.quarantine /Applications/ParCAD.app once. The Windows installer is not signed yet: SmartScreen warns, *More info*, then *Run anyway*. Every platform also has a parcad-cli-* archive — parcad, its worker beside it and the seed parts — for running the host without a window. Keep the two binaries together.
macOS, Linux and Windows. Day-to-day development is on macOS; the release workflow builds and measures on all three, and Linux on arm64 builds too.
You need Rust (the toolchain is pinned; rustup honours it), Bun, CMake, a C++ compiler, patch(1) and Python 3.11+. A full build wants around 20 GB free. On Linux the window also needs WebKitGTK (libwebkit2gtk-4.1-dev), and libclang-dev for the script sandbox's bindings. On Windows, use MSVC (Visual Studio Build Tools) and run the scripts from Git Bash, which also provides patch.
cd app && bun install --frozen-lockfile && cd .. # first: the Rust build shells out to bun
cargo build --locked --release tools/build-worker.sh --release # the exact kernel — ~5 min on 14 cores, once cd app && bun run tauri dev
cargo build produces a *dev* app whatever the profile — Tauri's switch is the custom-protocol feature, not --release — so launch the window through tauri dev or tauri build, never the bare binary. And a root cargo build deliberately does not build OpenCASCADE; tools/build-worker.sh does.
tools/check.sh # everything that gates a change (~5 min)
tools/check.sh --fast # the kernel crates and the editor tests (~4 s)
Or headless:
bun tools/run.ts examples/bracket.js > /tmp/bracket.json
./target/release/parcad /tmp/bracket.json --out out --step out/part.step
The app serves its UI and an MCP endpoint on http://127.0.0.1:4242. Parts live in ~/Library/Application Support/parcad as plain .js files you can edit anywhere.
With nothing installed: open ParCAD web, choose Connect your AI, and give your client the link it shows — Claude Code, the Claude app as a custom connector, Cursor, VS Code, or any client that connects to a URL. The tab is the server, with the same tools as the app, and it has to stay open; a relay passes the messages and keeps none (relay/README.md).
Every route below runs the same parcad on your machine: the one Homebrew installs, which the desktop app carries too. Install either first.
As a plugin, which brings the MCP server and a skill that says how to use it:
/plugin marketplace add ierehon1905/parcad
/plugin install parcad@parcad
In Codex, which finds parcad on PATH, so the Homebrew install:
codex plugin marketplace add ierehon1905/parcad
codex plugin add parcad@parcad
In Cursor or VS Code, with parcad on PATH:
Or add the server by hand, in any client that launches stdio servers:
claude mcp add parcad -- parcad mcp
codex mcp add parcad -- parcad mcp
parcad mcp relays to the app or parcad serve when one is running, so the agent shares the live session with your window. When none is running it hosts one itself, for as long as the client stays connected. A client that connects by URL can use http://127.0.0.1:4242/mcp directly, but only while a host is up; brew services start parcad keeps one up from login.
The same tools are on the command line, with the same names and arguments — parcad tools lists them, parcad call evaluate_part --set script=@part.js calls one — and they work whether or not the app is open.
ParCAD is also in the official MCP Registry as io.github.ierehon1905/parcad, so clients that browse it can install it by that name.
Start the agent on the read_docs tool, which hands over the whole language in one call.
ParCAD collects nothing about you: no accounts, no analytics, no telemetry. PRIVACY.md lists everything that touches the network.
ParCAD is free software under the GNU AGPL-3.0 or later: use it, change it and share it, but a modified ParCAD you distribute or run as a service must publish its source too. The parts you make are yours — part scripts and everything ParCAD exports from them can be licensed however you like, and the seed parts in examples/ are MIT. Releases through v0.0.9 stay MIT or Apache-2.0.
Built on components under other licences: OpenCASCADE and its bindings under vendor/ are LGPL-2.1, and one file of our own, crates/parcad-core/src/occlusion.rs, is MPL-2.0 because it was ported from fidget. Building from source is unencumbered; redistributing a binary carries obligations — NOTICE.md spells them out, including how to swap in your own OpenCASCADE.
This software makes use of facilities provided by the Open CASCADE Technology software.