Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
作者提供的说明(英文原文)
TokenLab MCP server: generate images and video, call models. 32 default and 89 full-profile tools.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
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_TOKEN标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 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"
}
}
}
}在终端中运行这条命令
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-server运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.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"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"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"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
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 env这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日
注册名称已通过 GitHub 账户 hedging8563 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
你需要填写:TOKENLAB_API_KEY, TOKENLAB_MANAGEMENT_TOKEN
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.6.44)于昨天进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:Figma Context MCP, Claude Real Video, Figma MCP Server
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
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.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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
只显示了开头部分;其余内容请在仓库中阅读