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)
Run any Relay model (image, video, audio, LLM), poll tasks, upload files and search Relay's docs.
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。
RELAY_API_KEY, X-API-Key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 …”。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"relaygpu": {
"command": "npx",
"args": [
"-y",
"@relaygpu/mcp"
],
"env": {
"RELAY_API_KEY": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add --transport http relaygpu https://mcp.relaygpu.com/mcp --header 'X-API-Key: your-value'claude mcp add relaygpu --env RELAY_API_KEY=your-value -- npx -y @relaygpu/mcp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": {
"relaygpu": {
"url": "https://mcp.relaygpu.com/mcp",
"headers": {
"X-API-Key": "your-value"
}
}
}
}粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"relaygpu": {
"command": "npx",
"args": [
"-y",
"@relaygpu/mcp"
],
"env": {
"RELAY_API_KEY": "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": {
"relaygpu": {
"type": "http",
"url": "https://mcp.relaygpu.com/mcp",
"headers": {
"X-API-Key": "your-value"
}
}
}
}粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"relaygpu": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@relaygpu/mcp"
],
"env": {
"RELAY_API_KEY": "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。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
你的选择通过 Cookie 保存在这台设备上,无需账户。
X-API-Key 机密 必填 HTTP header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。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
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
注册名称已通过域名 relaygpu.com 验证(注册中心会核实域名所有权)
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
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
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:RELAY_API_KEY, X-API-Key
两种方式都可以:安装在你的电脑上,或者连接云端版本。
GitHub 仓库最后更新于–,最新版本(0.1.8)于13天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
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。
Relay's MCP server. Your agent can find a Relay model, read its input schema, run it, poll long tasks, upload files, run workflows and search the Relay docs, all from Claude Code, Cursor, VS Code or Claude Desktop. It is built on @relaygpu/client. The tools are generic and take the model as a string, so a model added to Relay works without a new release.
Connect to the hosted server, or run it locally:
| How | Credential | |
|---|---|---|
| Hosted (Streamable HTTP) | https://mcp.relaygpu.com/mcp, nothing to install | X-API-Key: relay_sk_... header, or Authorization: Bearer |
| Local (stdio) | npx -y @relaygpu/mcp (Node ≥ 20) | RELAY_API_KEY=relay_sk_... in its environment; optional RELAY_BASE_URL (default https://relaygpu.com) |
The server never stores your key: the hosted one reads it from each request and uses it for that request only, the local one reads it from its environment.
Claude Code, Codex, Cursor and VS Code connect to the hosted server: no Node, no npx. Claude Desktop accepts remote servers only through OAuth, which v0 does not offer yet, so it uses the local server through a one-click bundle. Every client can also run the local server; see Local server.
Terminal, in the CLI or the VS Code / JetBrains extension alike:
claude mcp add --transport http --scope user relay https://mcp.relaygpu.com/mcp --header "X-API-Key: relay_sk_..."
--scope user makes it available in every project; without it the server exists only in the directory you ran the command in. Check it with /mcp in a new session. If the terminal answers command not found: claude, the extension is installed but the CLI is not: install it with curl -fsSL https://claude.ai/install.sh | bash (or npm install -g @anthropic-ai/claude-code).
Codex sends the key as a Bearer token from an environment variable, so the key stays out of config.toml. Set RELAY_API_KEY in your shell profile, then:
codex mcp add relay --url https://mcp.relaygpu.com/mcp --bearer-token-env-var RELAY_API_KEY
The button installs the entry below with a placeholder key; replace relay_sk_... in Cursor's MCP settings afterwards. By hand: ~/.cursor/mcp.json (all projects) or .cursor/mcp.json (one project).
{
"mcpServers": { "relay": { "url": "https://mcp.relaygpu.com/mcp", "headers": { "X-API-Key": "relay_sk_..." } } } }
This installs the server for VS Code's own agent (Copilot Chat). Using Claude Code inside VS Code? Use the Claude Code command instead: the Claude Code extension does not read VS Code's MCP config.
VS Code asks for the key once and keeps it in its secret storage. By hand, in .vscode/mcp.json (one workspace) or with MCP: Open User Configuration (every workspace):
{
"inputs": [{ "type": "promptString", "id": "relay-key", "description": "Relay API key (relay_sk_...)", "password": true }], "servers": { "relay": { "type": "http", "url": "https://mcp.relaygpu.com/mcp", "headers": { "X-API-Key": "${input:relay-key}" } } } }
relay.mcpb.The bundle runs on Claude Desktop's built-in Node, so nothing else needs to be installed. get_credits and get_usage read the account, so they take a dashboard JWT or a custom-tier superkey, never a plain key; every other tool works with a plain key.
By hand instead: Settings → Developer → Edit Config opens claude_desktop_config.json in your default editor. Add the block below at the top level, save, then quit Claude Desktop (⌘Q) and reopen it:
{
"mcpServers": { "relay": { "command": "npx", "args": ["-y", "@relaygpu/mcp"], "env": { "RELAY_API_KEY": "relay_sk_..." } } } }
Any client can run the server on your machine instead; it needs Node 20 or newer on the PATH the client sees (see Troubleshooting).
claude mcp add relay --scope user --env RELAY_API_KEY=relay_sk_... -- npx -y @relaygpu/mcp
codex mcp add relay --env RELAY_API_KEY=relay_sk_... -- npx -y @relaygpu/mcp
Cursor (~/.cursor/mcp.json) and VS Code take the same command / args / env entry as the Claude Desktop block above; VS Code adds "type": "stdio" and lists it under "servers".
Ready-to-copy files are in examples/.
"command": run which npx in a terminal and paste the result (for example /Users/you/.nvm/versions/node/v22.22.0/bin/npx)."command" at a newer npx.npx, use "command": "cmd" with "args": ["/c", "npx", "-y", "@relaygpu/mcp"].npx downloads the package once (about 5 s); later starts take about 1 s.Tools marked *keyless* work without a credential on the local server. Keyless tools answer the public catalog; with a credential, search_models, get_model, get_pricing, estimate_cost and run_model's model lookup answer your account's: the models your tier and grants can run appear and run. The others are billed or account tools and need one. A hosted server with OAuth on (see Self-hosting) takes no request without a credential, keyless tools included.
| Tool | What it does | Example |
|---|---|---|
search_models *keyless* | Find models by tag and/or text; image-to-image also lists every image model that takes an input image (accepts: ["image"]) | "Find a text-to-video model from Kling" → {tag: "text-to-video", query: "kling"} |
get_model *keyless* | Route, request schema, example, pricing and status of one model | {model: "Qwen/qwen-image"} |
get_pricing *keyless* | Prices (public; your account's with a credential) for one model or all of them, including the media_storage SKUs | {model: "KlingTeam/v3-T2V"} |
estimate_cost *keyless* | Estimate from the price list (public; your account's with a credential; not an invoice) | {model: "KlingTeam/v3-T2V", usage: {duration_seconds: 5, quality_mode: "std"}} |
run_model | Run any model by name and wait up to 45 s | {model: "Qwen/qwen-image", input: {prompt: "a red fox", size: "512x512"}} |
check_task *keyless* | Poll a task (waits up to 30 s) | {task_id: "direct:…", wait_seconds: 30} |
upload_file | Host a file and get a URL for any *_url input (or an image editor's image), or a one-time upload slot for a local file on the hosted server | {path: "./clip.mp4", retention: "relay1d"} · {slot: true} |
list_workflows | List the workflow templates | "Which workflows can I run?" |
run_workflow | Start a workflow run, wait up to 45 s | {workflow_id: "script-voiceover", inputs: {messages: [{role: "user", content: "a lighthouse at dusk"}], voice: "Cherry"}} |
check_workflow_run *keyless* | Poll a run (waits up to 30 s) | {run_id: "…", wait_seconds: 30} |
cancel_workflow_run | Cancel a run that is still in progress | {run_id: "…"} |
get_credits | Credit balance, promos and consumption (JWT or custom-tier superkey) | "How many credits do I have left?" |
get_usage | Usage analytics (JWT or custom-tier superkey) | {period: "7d"} |
search_docs *keyless* | Search the Relay docs | {query: "idempotency key"} |
The hosted server cannot read files on your computer. How a local file reaches a model, per client:
| Client | Local file → model |
|---|---|
| Claude Code, Cursor, VS Code, Codex (hosted server) | upload_file({slot: true}) returns a curl line; the agent runs it in your shell with the file's path (no key in the shell, single use, 10 minutes) and it prints the file's url; pass that url to run_model (for example as image). |
| claude.ai, Claude Desktop, ChatGPT | upload_file({slot: true}) returns a link: open the link in your browser, pick the photo, and paste the link the page shows back into the chat; the model passes it to run_model. No key leaves the chat, single use, 10 minutes. A public URL of the file works too. |
| Local server (stdio), any client | upload_file({path: "./photo.png"}) uploads the file and returns its url. |
Image editors: search_models({tag: "image-to-image"}) lists every image model that takes an input image, each with accepts: ["image"].
tools/list and the keyless tools answer without a credential. A hosted server with OAuth on answers every /mcp request without a credential with 401 and WWW-Authenticate: Bearer resource_metadata="…", scope="relay", which is how clients start the "Connect Relay" sign-in; X-API-Key and Authorization: Bearer keep working there. A billed tool called without one returns a MISSING_CREDENTIALS tool error that names what to set: the X-API-Key header (hosted) or RELAY_API_KEY (stdio). Errors from Relay come back as tool errors that include the error class, code, requestId and the server's detail. Your key never appears in a tool result or a log line.run_model waits up to 45 s (wait_seconds, 0–45). If the task is still running after that, it returns the task_id and the line "Do not resubmit: call check_task with this task_id". Every submit carries an Idempotency-Key, so a retry does not bill twice. Pass your own idempotency_key if your agent might send the same submit again. Since 0.1.7 every model whose input schema takes async (image, video, audio) is submitted as a task, so a long image run returns a task_id, never a 524; chat models still answer inline.store_output with a media_storage SKU from get_pricing (for example relay7d). That SKU adds a per-file fee.urls); the server returns those links in place of the base64, for 1 h or the store_output lifetime. A result that carries base64 without a Rel只显示了开头部分;其余内容请在仓库中阅读