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)
Run any Relay model (image, video, audio, LLM), poll tasks, upload files and search Relay's docs.
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.
RELAY_API_KEY, X-API-KeyAls geheim markierte Werte sind Schlüssel zu deinem Konto. Gib sie nie weiter und füge sie nie in einen Chat ein.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Diese Adresse braucht einen Schlüssel in einem Header der Anfrage, und das Menü zum Hinzufügen von Connectors kann ihn nicht setzen. Nutze stattdessen Claude Code, Cursor oder VS Code.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"relaygpu": {
"command": "npx",
"args": [
"-y",
"@relaygpu/mcp"
],
"env": {
"RELAY_API_KEY": "your-value"
}
}
}
}Führe das in deinem Terminal aus
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/mcpTrag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"relaygpu": {
"url": "https://mcp.relaygpu.com/mcp",
"headers": {
"X-API-Key": "your-value"
}
}
}
}In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"relaygpu": {
"command": "npx",
"args": [
"-y",
"@relaygpu/mcp"
],
"env": {
"RELAY_API_KEY": "your-value"
}
}
}
}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.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"relaygpu": {
"type": "http",
"url": "https://mcp.relaygpu.com/mcp",
"headers": {
"X-API-Key": "your-value"
}
}
}
}In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"relaygpu": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@relaygpu/mcp"
],
"env": {
"RELAY_API_KEY": "your-value"
}
}
}
}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.
Diese Adresse braucht einen Schlüssel in einem Header der Anfrage, und das Menü zum Hinzufügen von Connectors kann ihn nicht setzen. Nutze stattdessen Claude Code, Cursor oder VS Code.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
X-API-Key geheim erforderlich HTTP headerDiese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Die Tool-Liste dieses Servers haben wir noch nicht gelesen; wir prüfen die Endpunkte reihum.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026
Der Registry-Name wurde über die Domain relaygpu.com bestätigt (die Registry prüft, wem die Domain gehört)
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Noch nicht geprüft; wir prüfen die Endpunkte reihum
Noch nicht geprüft; wir prüfen die Endpunkte reihum
Noch nicht geprüft; wir lesen die Tool-Liste, wenn wir den Endpunkt prüfen
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.
Das musst du eintragen: RELAY_API_KEY, X-API-Key
Beides geht: Installiere ihn auf deinem Computer oder verbinde dich mit der Cloud-Version.
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.1.8) kam vor 13 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Er verbindet sich per URL, also funktionieren auch Apps, die Remote-MCP-Server akzeptieren, zum Beispiel ChatGPT im Entwicklermodus.
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.
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 RelNur der Anfang wird gezeigt; den Rest findest du im Repo