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)
TokenLab MCP server: generate images and video, call models. 32 default and 89 full-profile tools.
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.
TOKENLAB_API_BASE, TOKENLAB_API_KEY, TOKENLAB_REQUEST_TIMEOUT_MS, TOKENLAB_MCP_TOOL_PROFILE, TOKENLAB_MCP_SCHEMA_MODE, TOKENLAB_MCP_MAX_FILE_BYTES, TOKENLAB_MCP_INLINE_BYTES, TOKENLAB_ARTIFACT_DIR, TOKENLAB_MANAGEMENT_TOKENLos valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"tokenlab": {
"command": "npx",
"args": [
"-y",
"@tokenlabai/mcp-server"
],
"env": {
"TOKENLAB_API_BASE": "your-value",
"TOKENLAB_API_KEY": "your-value",
"TOKENLAB_REQUEST_TIMEOUT_MS": "your-value",
"TOKENLAB_MCP_TOOL_PROFILE": "your-value",
"TOKENLAB_MCP_SCHEMA_MODE": "your-value",
"TOKENLAB_MCP_MAX_FILE_BYTES": "your-value",
"TOKENLAB_MCP_INLINE_BYTES": "your-value",
"TOKENLAB_ARTIFACT_DIR": "your-value",
"TOKENLAB_MANAGEMENT_TOKEN": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add tokenlab --env TOKENLAB_API_BASE=your-value --env TOKENLAB_API_KEY=your-value --env TOKENLAB_REQUEST_TIMEOUT_MS=your-value --env TOKENLAB_MCP_TOOL_PROFILE=your-value --env TOKENLAB_MCP_SCHEMA_MODE=your-value --env TOKENLAB_MCP_MAX_FILE_BYTES=your-value --env TOKENLAB_MCP_INLINE_BYTES=your-value --env TOKENLAB_ARTIFACT_DIR=your-value --env TOKENLAB_MANAGEMENT_TOKEN=your-value -- npx -y @tokenlabai/mcp-serverCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"tokenlab": {
"command": "npx",
"args": [
"-y",
"@tokenlabai/mcp-server"
],
"env": {
"TOKENLAB_API_BASE": "your-value",
"TOKENLAB_API_KEY": "your-value",
"TOKENLAB_REQUEST_TIMEOUT_MS": "your-value",
"TOKENLAB_MCP_TOOL_PROFILE": "your-value",
"TOKENLAB_MCP_SCHEMA_MODE": "your-value",
"TOKENLAB_MCP_MAX_FILE_BYTES": "your-value",
"TOKENLAB_MCP_INLINE_BYTES": "your-value",
"TOKENLAB_ARTIFACT_DIR": "your-value",
"TOKENLAB_MANAGEMENT_TOKEN": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"tokenlab": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@tokenlabai/mcp-server"
],
"env": {
"TOKENLAB_API_BASE": "your-value",
"TOKENLAB_API_KEY": "your-value",
"TOKENLAB_REQUEST_TIMEOUT_MS": "your-value",
"TOKENLAB_MCP_TOOL_PROFILE": "your-value",
"TOKENLAB_MCP_SCHEMA_MODE": "your-value",
"TOKENLAB_MCP_MAX_FILE_BYTES": "your-value",
"TOKENLAB_MCP_INLINE_BYTES": "your-value",
"TOKENLAB_ARTIFACT_DIR": "your-value",
"TOKENLAB_MANAGEMENT_TOKEN": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
TOKENLAB_API_BASE envTOKENLAB_REQUEST_TIMEOUT_MS envTOKENLAB_MCP_TOOL_PROFILE envTOKENLAB_MCP_SCHEMA_MODE envTOKENLAB_MCP_MAX_FILE_BYTES envTOKENLAB_MCP_INLINE_BYTES envTOKENLAB_ARTIFACT_DIR envEsta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
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 6 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub hedging8563, 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.
Debes completar: TOKENLAB_API_KEY, TOKENLAB_MANAGEMENT_TOKEN
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 (0.6.44) llegó al registro ayer.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
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:★ 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.
OpenAPI-generated Model Context Protocol server for TokenLab public model discovery, pricing, native LLM endpoints, typed decisions, multimodal generation, async tasks, files, embeddings, rerank, translation, resources, prompts, and the broader developer API.
It exposes public catalog tools for agents that need to choose models, inspect supported request formats, or compare pricing before calling TokenLab APIs. Credentialed tools cover text inference, image generation and editing, video, music, 3D, async task polling, embeddings, rerank, typed decisions, and text translation.
The checked-in generated/tools.json manifest is generated from TokenLab's public OpenAPI document plus the small MCP-only overlay in contract/mcp-overlay.json. Version 0.6.44 generates 87 endpoint tools; with the two MCP-only composite discovery tools, the full profile returns 89 tools from tools/list.
| Profile | Endpoint tools | Total registered tools | Model-facing schema | Coverage |
|---|---|---|---|---|
catalog | 4 | 6 | Exact | Public model discovery and pricing only; no API key required |
core (default) | 30 | 32 | Portable | Catalog and pricing; Chat Completions, Responses, Anthropic Messages, Gemini generateContent; System One typed decisions; images, video, music, 3D, speech and transcription; async tasks; files; embeddings, rerank, and translation |
full | 87 | 89 | Portable | Every allowlisted developer API operation in the checked-in OpenAPI snapshot, including core plus response lifecycle, batches, worlds, and native model discovery |
The total registered count is the number returned by tools/list. All profiles include compare_models and get_api_overview, producing totals of 6, 32, and 89 tools. Realtime and streaming-only operations are excluded because stdio MCP tool calls return one final result. API operations that accept stream fix it internally to false without exposing a boolean const to provider adapters, and the Gemini query-string API key is intentionally hidden from tool arguments. create_gemini_content exposes the camelCase Gemini fields (systemInstruction, generationConfig, safetySettings, toolConfig, cachedContent) and hides their snake_case proto spellings, which the API accepts as aliases.
The portable projection keeps every top-level argument but bounds deeply nested model-facing shapes. The server still validates calls against the complete generated OpenAPI schema before issuing an API request. Compatibility budgets keep core at no more than 60 KB and depth 8, and full at no more than 115 KB and depth 8 for the complete tools/list response. Tests also run the full profile through the Google AI SDK version used by the observed OpenCode/Gemini failure and keep its function declarations within 90 KB.
Set TOKENLAB_MCP_TOOL_PROFILE=catalog for the smallest public-only tool list or TOKENLAB_MCP_TOOL_PROFILE=full for the broad developer API. Set TOKENLAB_MCP_SCHEMA_MODE=exact only when a client needs the complete nested JSON Schema and can accept its larger/deeper tool payload. Use strict for providers that require every property to be listed in required and every object to set additionalProperties: false; complex top-level arguments are represented as JSON-encoded strings and decoded before canonical validation. Canonical tool names, descriptions, input JSON Schemas, HTTP bindings, content types, auth requirements, and task behavior can be inspected in generated/tools.json.
The smaller generated/public-contract.json is the machine-readable projection used by TokenLab's website and other public consumers. It contains package identity, profile counts, core tool layers, resources, prompts, and source hashes without copying all endpoint schemas.
structuredContent while retaining serialized text for older clients.exact mode is byte-shape equivalent to the generated canonical schema.choose_tokenlab_model and build_tokenlab_request prompts guide agents to use live model truth and preserve native endpoint shapes.npm install
npm start
Install from npm:
npx -y @tokenlabai/mcp-server
Agent-assisted installers can follow llms-install.md for a credential-safe setup and verification flow.
Run in Docker:
docker build -t tokenlab-mcp-server .
docker run --rm -i tokenlab-mcp-server
Add -e TOKENLAB_API_KEY when using credentialed API tools. Public catalog tools do not require a key.
Claude Desktop style config:
{
"mcpServers": { "tokenlab-model-catalog": { "command": "npx", "args": ["-y", "@tokenlabai/mcp-server"], "env": { "TOKENLAB_API_BASE": "https://api.tokenlab.sh" } } } }
No TokenLab API key is required for public catalog and pricing operations. Set TOKENLAB_API_KEY when credentialed tools should call TokenLab APIs. Generated tools preserve the OpenAPI request shape for OpenAI-compatible and native endpoints instead of flattening them into a shared prompt format.
Multipart operations accept local file paths. Small image and audio responses are returned as native MCP content; larger or other binary responses are written to TOKENLAB_ARTIFACT_DIR and returned as a path with MIME type and byte count.
Video, music, and 3D creation tools always return an async task. Image generation and editing may return a completed result or an async task depending on the selected model and request.
Media tools preserve the complete TokenLab API response under response and add a normalized delivery summary:
{
"delivery": { "mode": "async", "task_id": "ldtask_...", "status": "pending", "poll_url": "/v1/tasks/ldtask_...", "terminal": false, "next_tool": "get_task_status" }, "response": {} }
Use delivery.mode instead of assuming all image requests are synchronous. For async tasks, call get_task_status with { "id": delivery.task_id } until delivery.terminal is true. Completion is determined from status, not from an optional progress field.
TOKENLAB_API_BASE: optional, defaults to https://api.tokenlab.shTOKENLAB_API_KEY: optional; required for text inference, multimodal generation, async task, embedding, rerank, decision, and translation toolsTOKENLAB_MCP_TOOL_PROFILE: optional, catalog, core (default), or fullTOKENLAB_MCP_SCHEMA_MODE: optional, portable, exact, or strict; defaults to the selected profile's tested modeTOKENLAB_REQUEST_TIMEOUT_MS: optional request timeout in milliseconds, defaults to 120000TOKENLAB_MCP_MAX_FILE_BYTES: optional maximum local upload size per file, defaults to 104857600 (100 MiB)TOKENLAB_MCP_INLINE_BYTES: optional maximum binary/JSON response size returned inline, defaults to 2097152 (2 MiB)TOKENLAB_ARTIFACT_DIR: optional output directory for non-inline response artifacts, defaults to the OS temp directory under tokenlab-mcpFor Chat Completions image inputs, prefer byte-accurate data URLs such as data:image/png;base64,.... If an MCP caller labels a recognized PNG, JPEG, WebP, or GIF payload as application/octet-stream, the server corrects that generic MIME before forwarding. An unrecognized generic binary payload is rejected locally with a precise input error.
The public OpenAPI document is the API contract source. The overlay contains only MCP-specific choices: profile exposure, stable tool aliases, secret omission, non-streaming constraints, content-type variants, async task semantics, and the compact public projection consumed by the website and docs gates.
npm run contract:source-check # compare the snapshot with the live canonical OpenAPI (read-only)
npm run contract:check # check generated output against the checked-in snapshot (offline) npm run contract:sync # fetch OpenAPI and regenerate; refuses dirty outputs or a stale branch npm test # compile profiles and test exact/portable/strict schemas, provider conversion, routing, tasks, files, and binary output
Always run git pull --ff-only before a manual contract sync. contract:check proves internal consistency only; contract:source-check proves freshness against the canonical source. The scheduled Sync TokenLab OpenAPI contract workflow runs the full write sequence and commits only the verified OpenAPI snapshot and generated manifest to main. A failed fetch, stale local branch, dirty generated output, generation error, schema compilation error, or test leaves the tracked contract unchanged.
This repository includes server.json for the official MCP Registry.
Release metadata:
@tokenlabai/mcp-server@0.6.44io.github.hedging8563/tokenlabpackage.json.mcpName: io.github.hedging8563/tokenlabFor a new release:
package.json, package-lock.json, and server.json.v0.6.0.The same workflow can be run manually from main to republish only the current MCP Registry metadata. No npm or MCP Registry token is stored in GitHub.
Use the catalog profile when no credentialed tools are needed. Keep TOKENLAB_API_KEY in the local MCP client's secret environment, enable human confirmation for billable and destructive calls, and review tool annotations before granting persistent approval. Do not send a TokenLab API key to an untrusted hosted MCP server.
Each API request sends X-TokenLab-Client-Source: mcp- (for example mcp-create_image) so TokenLab can count which tools are used. Reading the tokenlab://api/overview resource sends mcp-resource-api_overview. The header holds only the lowercased tool name, cut to 64 characters, and no tool arguments.
Use the full profile to configure workspace webhooks with list_webhooks, create_webhook, get_webhook, update_webhook, delete_webhook, rotate_webhook_secret, test_webhook and list_webhook_deliveries.
Set `TOKENLAB_MANAGEMENT
Solo se muestra el principio; lee el resto en el repo