Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Descripción del creador (original en inglés)
AI drafting, design review and a drawing memory in BricsCAD on Linux: 128 tools, pure AutoLISP
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
El creador no incluyó detalles de instalación en el registro. Consulta el README del creador más abajo.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 10 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub Psalmustrack, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (1.3.0) llegó al registro hace 3 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code.
En la misma categoría: Figma Context MCP, Claude Real Video, Figma MCP Server
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:↓ Descargas por semanai★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
Let AI draw in your CAD. An MCP server for any AutoLISP-capable CAD — no COM, no SDK, no plugins. Pure AutoLISP. The reference adapter drives BricsCAD on Linux: the first MCP server for a professional DWG CAD on Linux.
*"Draw a DN80 flange: front view, hatched section, dimensions — then model it in 3D."*
*Real-time capture, unedited: front view with bolt circle, hatched section, radial/diameter dimensions, leader, title block — then the same flange modeled as a 3D solid with an AI-written parametric AutoLISP loop and one boolean subtraction. ~20 seconds, 12 tool calls.*
| Complete 2D drawing, drawn by Claude | 3D solids with booleans | Clean render for AI vision |
|---|---|---|
Every other MCP server for a professional DWG CAD (multiCAD-mcp, autocad-mcp, CAD-MCP, ...) talks to the CAD through Windows COM — none of them can run on Linux, and none of them does real 3D.
BricsCAD is the professional DWG CAD that *does* run natively on Linux. This server drives it through a mechanism that needs no API at all: an AutoLISP file bridge. The MCP server writes LISP expressions to a file, triggers a tiny MCP command inside the CAD, and reads the result back. That's the whole trick — and it unlocks everything the CAD can do, including 3D solid modeling.
Because the bridge is plain AutoLISP + standard DXF entmake + AutoCAD-compatible commands, it is portable by construction: AutoCAD, ARES Commander (also Linux-native!), ZWCAD, GstarCAD and the IntelliCAD family all speak the same language. Porting means swapping the autoload file name and the keystroke trigger — adapters welcome.
MCP client (Claude, Cursor, ...) BricsCAD (Linux)
│ │ ▼ ▼ server.py (FastMCP, 128 tools) c:MCP AutoLISP command │ writes LISP ──► /tmp/mcp_bricscad.in │ triggers via xdotool ──► reads, evals line by line │ reads result ◄── /tmp/mcp_bricscad.out
slot, bolt_circle, rounded_rect, polygon, center_mark: one call, the server does the mathdraw_batch executes N operations in one round-trip, wrapped in one undo group (one batch = one Ctrl+Z)get_selection reads the GUI pickfirst set; select_by/select_window highlight what the AI found *before* acting; modify tools accept "selection"boolean_verified cuts *and measures* the change against the volume you expected (a cut that lands short reads SHORT, not success); overhang_report reads the STL mesh and says whether a part prints without supports, scoring all six orientations; contact_report over an assembly (assembly_place/assembly_list/assembly_clear) says who touches whom, who interferes, and who is an orphan — a part touching nothing, because its job was superseded and nobody noticed; hole_report physically probes every hole and says which are actually open (a drawing lies about its holes until something checks); graph_build/graph_trace read the 2D geometry as a connectivity graph — separate networks, exact run lengths, and the open ends that are real breaks vs T-junctions, with the joining tolerance *emerging from the drawing* instead of hardcodedmemory_enable puts a journal beside the .dwg that the CAD writes by itself, catching the edits the *human* makes in the GUI while no tool is running; tag_entity gives entities semantic roles ("muro-nord", "asta-principale") keyed to handles, which survive save and reopen; world_report answers *what is here, what did I call it, what changed since I last looked* — and revalidates every claim against the live drawing before answering (an entity erased behind the AI's back reads DEAD (erased since tagging), reported, never hidden). The next prompt — or the next session — starts knowing the drawing instead of re-surveying itlambdacad://traps resource that costs nothing until readrender_view: BricsCAD's internal PNG render (clean, no UI, ~30 KB) for vision modelscreate_sheet (A4…A0, margins zeroed so paper mm = sheet mm), add_viewport (ask for 1:50 and it *is* 1:50 — measured back off the entity, and parked on a non-plotting layer), fit_viewport (measures what is drawn and picks the largest STANDARD scale that fits — 1:37 is not a scale), title_block (border + ISO 7200 cartouche, sized from the sheet), export_sheet_pdf, which checks its own work by measuring the page of the PDF it just wroteexport_stl: 3D solids straight to the slicer, parked on the origin)list_documents shows which one the tools are pointing at (plus unsaved changes and read-only), use_document picks another; every reply says which drawing answered, and warns when it changes underfootrun_lisp evaluates arbitrary AutoLISP (multi-line, multi-expression): capable models write parametric code and love itFull reference: docs/TOOLS.md · How it works: docs/ARCHITECTURE.md
| Metric | Result |
|---|---|
| Tool calls for a complete dimensioned flange | 200 → 22 (9× fewer round-trips vs primitive-per-call) |
| Trigger latency | 0.25 s per call |
| Error reporting | per-line LISP errors (msg=L2: ...) → models self-correct without screenshots |
| Exactness | entity_length on an r=20 circle: 125.664 / 1256.637 (2πr, πr² exact) |
Details and model-behavior notes (Sonnet writes parametric LISP, Haiku uses typed tools): docs/BENCHMARKS.md
BRICS_DISPLAY=:0 python tests/test_tools.py # ~135 checks incl. review + memory groups, ~2-4 min
python tests/test_tools.py 3d edges export # or just some groups python tests/test_tools.py --list
An integration suite: it drives the CAD you already have running, then measures what came out — closed-form volumes, bounding boxes, the value stored inside a dimension, triangle counts read out of the STL. Never "no error".
That distinction is the whole point. The bridge answers OK whenever the CAD accepted the command, which is not the same as the CAD having done what was asked. Every bug found so far was of that shape: the classic CHAMFER silently switching to *all edges*; a layout that plots rotated 90°, so an A3 landscape sheet comes out portrait, the drawing falls off the paper and the export writes a perfectly valid, entirely empty page; and — the one that reached a release — running object snap dragging programmatic coordinates onto nearby geometry, so five blocks placed in a row each landed on the previous. A volume, a bounding box, a measured dimension and the page of a PDF are exact signatures: every one of those surfaced as arithmetic that did not add up.
The suite draws in a scratch region (x ≥ 50000), erases it afterwards, and fails if the entity count does not come back to where it started. It still works in the active drawing, so point it at a scratch one.
With 128 tools, the interesting question is which ones earn their place — and which fail often enough to signal a docstring or design problem. The server appends one JSON line per call to ~/.lambdacad/usage.jsonl:
{"t": 1786526823.4, "tool": "draw_batch", "ms": 198, "err": 0}
Tool name, duration, error flag. Never the arguments — no coordinates, no paths, no drawing data — and nothing ever leaves your machine. Disable with LAMBDACAD_TELEMETRY=0.
python scripts/usage_report.py # per-tool calls, error rate, p50
python scripts/usage_report.py --core 95 # smallest set covering 95% of calls python scripts/usage_report.py --reset # archive the current log
The --core output is a data-driven candidate for CORE_TOOLS (compact mode): after a few weeks of real use, the choice of which tools deserve a place in a schema-limited client stops being a guess. Early signal from the integration suite itself: run_lisp alone is ~half of all calls — on clients that load schemas on demand (Claude Code's tool search), the long tail of typed tools costs nothing until used, so the rich docstrings stay.
Requirements: Linux, BricsCAD (any recent version — tested on V26), Python 3.10+, xdotool.
git clone https://github.com/Psalmustrack/lambdacad-mcp
cd lambdacad-mcp ./install.sh
The installer creates a venv, installs the AutoLISP bridge into BricsCAD's Support/on_doc_load.lsp (idempotent, marker-delimited), and prints ready-to-paste config for Claude Code / Claude Desktop.
Then:
bricscad tools appear.| Variable | Default | Purpose |
|---|---|---|
BRICS_DISPLAY | session $DISPLAY | X display where BricsCAD runs (e.g. :77 for a nested Xephyr) |
BRICS_COMPACT | off | 1 = expose only 14 essential tools (~1k schema tokens instead of ~7k) for clients that inject every schema |
BRICS_MCP_IN / BRICS_MCP_OUT | /tmp/mcp_bricscad.{in,out} | bridge file paths |
run_lisp and run_command execute arbitrary code inside BricsCAD by design — that's what makes the server fully general. O
Solo se muestra el principio; lee el resto en el repo