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)
Generate video, images, audio and speech with Vidofy — Veo 3.1, Kling 3.0, Flux 2 and 570+ models.
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.
VIDOFY_TOKENAls 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.
Funktioniert in Claude im Web, auf dem Desktop und auf dem Handy:
https://vidofy.ai/mcp-appÖffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"vidofy": {
"command": "npx",
"args": [
"-y",
"@vidofy/mcp"
],
"env": {
"VIDOFY_TOKEN": "your-value"
}
}
}
}Führe das in deinem Terminal aus
claude mcp add --transport http vidofy https://vidofy.ai/mcp-appclaude mcp add vidofy --env VIDOFY_TOKEN=your-value -- npx -y @vidofy/mcpTrag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"vidofy": {
"url": "https://vidofy.ai/mcp-app"
}
}
}In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"vidofy": {
"command": "npx",
"args": [
"-y",
"@vidofy/mcp"
],
"env": {
"VIDOFY_TOKEN": "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": {
"vidofy": {
"type": "http",
"url": "https://vidofy.ai/mcp-app"
}
}
}In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"vidofy": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@vidofy/mcp"
],
"env": {
"VIDOFY_TOKEN": "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.
ChatGPT verbindet sich nur mit Servern im Internet:
https://vidofy.ai/mcp-appMenünamen können sich je nach Tarif und mit der Zeit leicht unterscheiden.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese 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 vidofy.ai 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: VIDOFY_TOKEN
Beides geht: Installiere ihn auf deinem Computer oder verbinde dich mit der Cloud-Version.
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.1.3) kam vor 11 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.
MCP server for [Vidofy](https://vidofy.ai) — generate images, video, audio and speech from Claude, ChatGPT, VS Code, Gemini CLI, Cursor, Hermes, or any MCP client, billed to your own Vidofy account, at the same prices the website charges.
Over 570 models, including Veo 3.1, Kling 3.0, Flux 2, Seedance 2.5, Wan 2.7, Hailuo 2.3, Runway, Luma Ray 2, Qwen Image 3.0, Vidu Q3 and LTX 2 — text-to-video, image-to-video, text-to-image, image editing, video and photo effects, lipsync, text-to-speech and voice cloning. The agent browses the catalogue, prices a generation before running it, and follows one to its result.
Status: first public release.
This server is for personal Vidofy accounts. It takes one credential,
VIDOFY_TOKEN, and spends your own coins — the same balance the website
spends, at the same prices. There is no other billing mode:
VIDOFY_API_KEYis
refused at startup, and that is a decision, not a feature waiting on a release.
| Tool | What it does | Spends |
|---|---|---|
list_modes | What Vidofy can generate: text-to-image, image-to-video, lipsync, speech… | no |
list_models | The models in one mode, with each one's credit cost and rough duration | no |
get_model | One model's full input contract: a JSON Schema, its file slots and their limits | no |
estimate_cost | What a generation will cost, before running it | no |
| `generate` | Runs it. The only tool that spends the balance. | yes |
get_status | Whether a generation has finished | no |
get_result | The finished media | no |
get_balance | Coins left, and how many expire with the subscription | no |
get_usage | Recent generations and what they cost | no |
The usual order is list_modes → list_models → get_model → estimate_cost → generate → get_status → get_result.
generate is the only tool without readOnlyHint, which is what tells a client to ask the user before running it. It charges at submit, not on success, and returns immediately with an id — a generation takes from ~30 seconds to several minutes, so the agent polls get_status rather than holding the call open. Output is private by default; pass public: true only when the user asked for a permanent public link.
File inputs take a path on the machine running the server. The package reads the user's own file and streams it with the submit — it never makes a temporary copy — and checks the extension and size against that model's own limits first, so a file the server would reject never leaves the disk.
Not exposed, deliberately: checkout, auto top-up, purchases, referrals, the daily reward. Nothing in this package can buy coins or change a plan, however it is prompted.
There are two ways in. Take the first one unless your client cannot do it.
Give your client this URL:
https://vidofy.ai/mcp-app
You sign in in your browser and approve once. No token to copy, nothing to keep in a config file, and nothing to update when this package changes.
| Client | How |
|---|---|
| Claude.ai · Claude Desktop | Settings → Connectors → *Add custom connector* → paste the URL → Connect, then approve the sign-in. They share one list: add it in either and it appears in both. Available on every plan, including Free — where you get one connector. |
| ChatGPT | Settings → Connectors → add a custom connector (no such option? turn on Developer Mode in Settings first) → paste the URL → Connect, then approve. On a Business or Enterprise workspace an administrator adds it for everyone. |
| VS Code | Add an MCP server of type http with the URL above, then approve the sign-in in your browser. VS Code identifies itself with its own published client metadata, so there is nothing to register and no client secret to obtain. |
| Claude Code · Codex · Cursor | Each accepts a remote MCP server URL. Follow that client's own MCP documentation and give it the URL above. |
Then ask it: *"list Vidofy modes"* to confirm the connection, and *"make me a 5-second clip of a red bicycle"* — it prices the generation before running it.
Some clients cannot take this route, and it is worth knowing why before you try. Signing in here needs a client that identifies itself with a published metadata document — an https URL the authorization server fetches. Clients that instead expect to register themselves at a registration_endpoint, or to be handed a client_id and client_secret you created by hand, have nothing to work with: this server issues neither. Gemini CLI and Hermes are both in that group today. Take route 2 — it is not a lesser path, just a different way of proving who you are.
Create a personal MCP token at vidofy.ai → Studio → Account → MCP Access. It is shown once.
// claude_desktop_config.json (Cursor: .cursor/mcp.json — same shape)
{ "mcpServers": { "vidofy": { "command": "npx", "args": ["-y", "@vidofy/mcp"], "env": { "VIDOFY_TOKEN": "vmt_..." } } } }
npx fetches it on first run. Prefer a pinned copy? npm i -g @vidofy/mcp, then:
{ "command": "vidofy-mcp", "env": { "VIDOFY_TOKEN": "vmt_..." } }
The entry is the same everywhere — the file it goes in, and what the outer key is called, are not. Check yours against your client's own documentation before you paste:
| Client | File | Outer key |
|---|---|---|
| Claude Desktop | claude_desktop_config.json | mcpServers |
| Cursor | .cursor/mcp.json | mcpServers |
| Gemini CLI | settings.json, user-level or per project | mcpServers |
| VS Code | .vscode/mcp.json, or the user-profile mcp.json | `servers` — and each entry adds "type": "stdio" |
| Hermes | config.yaml in the Hermes home directory | mcp_servers — YAML, not JSON |
So VS Code wants:
// .vscode/mcp.json
{ "servers": { "vidofy": { "type": "stdio", "command": "npx", "args": ["-y", "@vidofy/mcp"], "env": { "VIDOFY_TOKEN": "vmt_..." } } } }
and Hermes wants the same thing in YAML:
mcp_servers:
vidofy: command: npx args: ["-y", "@vidofy/mcp"] env: VIDOFY_TOKEN: "vmt_..."
Both paths reach the same account, the same models and the same balance. The difference is only where the process runs and how you prove who you are.
One client shows more than the others. A generation normally comes back as text the model reads out. A host that supports MCP Apps gets a live card instead — the picture or clip itself, its progress while it runs, and a download button — and the server offers it only to a host that says it can render one. Claude and VS Code both do (in VS Code, turn on chat.mcp.apps.enabled). Everywhere else the same result arrives as text and, for an image, an inline picture. Nothing is missing; it is just quieter.
| Variable | Required | What it does |
|---|---|---|
VIDOFY_TOKEN | yes | Personal MCP token (vmt_…). Spends your own Vidofy coins, exactly as the studio does. |
VIDOFY_API_BASE | no | Override the origin the server talks to — an origin only, no path. Defaults to https://vidofy.ai, which is what you want. |
VIDOFY_API_KEY is recognised only in order to be refused: a vky_… key bills a different balance, which this server does not serve. Setting it stops startup with a message naming the token to use instead — and setting *both* is refused too, since the two bill different balances and no precedence rule is worth having to remember.
npm install
npm run build npm run inspect # MCP Inspector — spends nothing
VIDOFY_API_BASE points it at a different origin, if you are running one.
Nothing here writes to stdout. With stdio transport, stdout *is* the protocol channel — a single stray console.log() puts a non-JSON line in the stream and the client drops the connection with an error that explains nothing. Diagnostics go to stderr via the log() helper in src/index.ts.
src/config.ts credential + mode + base URL, validated at startup
src/backend.ts the only place that talks HTTP: auth, retries, multipart, errors src/schema.ts one model's m_options → a JSON Schema the agent can fill in src/map/b2c.ts both response shapes → one; strips the provider cost src/tools/info.ts list_modes, list_models, get_model src/tools/generation.ts estimate_cost, generate, get_status, get_result src/tools/account.ts get_balance, get_usage src/index.ts the server: stdio transport, tool registration, annotations
server.json MCP registry manifest (name must match package.json "mcpName")
MIT