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)
Image, video and audio generation APIs with USD quotes and confirmation before paid requests.
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.
SPICY_API_KEYLos 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": {
"spicyapi-ai": {
"command": "npx",
"args": [
"-y",
"@spicyapi/mcp"
],
"env": {
"SPICY_API_KEY": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add spicyapi-ai --env SPICY_API_KEY=your-value -- npx -y @spicyapi/mcpCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"spicyapi-ai": {
"command": "npx",
"args": [
"-y",
"@spicyapi/mcp"
],
"env": {
"SPICY_API_KEY": "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": {
"spicyapi-ai": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@spicyapi/mcp"
],
"env": {
"SPICY_API_KEY": "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.
Esta 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 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub spicyapi-ai, 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: SPICY_API_KEY
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 (0.6.2) llegó al registro hace 3 días.
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.
The official local MCP server for SpicyAPI. It lets the AI assistant you already use — Claude Desktop, Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI or any MCP client — browse the live model catalog, compare prices, create generation tasks and collect results, with every billable step confirmed by you.
SpicyAPI is an unrestricted AI API: one key for 200+ image, video, audio and chat models (Seedance, Kling, Wan, MiniMax, Seedream, GPT Image, Suno and more), with no content filter added by the platform. What a request can produce depends on the model you pick, and the catalog marks which models are uncensored.
This package installs spicyapi-mcp (stdio) and spicyapi-mcp-http (loopback-only Streamable HTTP). It does not contain the CLI or the Agent Skill.
Full, beginner-friendly guide: [docs.spicyapi.ai/docs/mcp](https://docs.spicyapi.ai/docs/mcp).
MCP (Model Context Protocol) is an open standard for giving AI assistants extra abilities. Once this server is added to your assistant, you can ask in ordinary language — _"make a five-second video from this photo"_ — and the assistant:
The server runs on your own computer. Your assistant app starts it when needed; there is nothing to host.
node --version). npx ships with Node.js.did not declare the required capability. Nothing is created, reserved, charged or destroyed: creation has fetched only its free quote by then, and retry and purge have sent no request. The read-only tools still work.0 for no cap.sk-spicy- and is shown once.export SPICY_API_KEY="sk-spicy-..." # paste your own key
In Windows PowerShell: $env:SPICY_API_KEY = "sk-spicy-...".
Every client below runs the same stdio server: npx --yes --package=@spicyapi/mcp spicyapi-mcp.
You never run this server yourself — your MCP client starts it. Launched by hand it just waits silently on stdin, which looks like a hang. And it needs --package=@spicyapi/mcp in front of the binary name, because this package ships two of them; plain npx @spicyapi/mcp fails with could not determine executable to run.
~/Library/Application Support/Claude/claude_desktop_config.json on macOS and %APPDATA%\Claude\claude_desktop_config.json on Windows.spicyapi entry to an existing mcpServers) and replace YOUR_SPICY_API_KEY.{
"mcpServers": { "spicyapi": { "command": "npx", "args": ["--yes", "--package=@spicyapi/mcp", "spicyapi-mcp"], "env": { "SPICY_API_KEY": "YOUR_SPICY_API_KEY" } } } }
claude mcp add spicyapi \
-e SPICY_API_KEY=$SPICY_API_KEY \ -- npx --yes --package=@spicyapi/mcp spicyapi-mcp
The default scope is the current project; add --scope user for every project. Do not use --scope project, which writes the key into a .mcp.json inside the repository. Check with claude mcp list or /mcp. On native Windows, if the server fails to start, use -- cmd /c npx --yes --package=@spicyapi/mcp spicyapi-mcp.
codex mcp add spicyapi \
--env SPICY_API_KEY=$SPICY_API_KEY \ -- npx --yes --package=@spicyapi/mcp spicyapi-mcp
That writes ~/.codex/config.toml, which the Codex CLI, the IDE extension and the ChatGPT desktop app all read — configure it once and all three pick it up. Check with codex mcp list or /mcp.
Both terminal commands copy SPICY_API_KEY out of your current shell into that client's local config, so run them in a terminal where the key is already exported. If it was not, remove the server (claude mcp remove spicyapi / codex mcp remove spicyapi) and add it again.
Cursor (~/.cursor/mcp.json), Windsurf (~/.codeium/windsurf/mcp_config.json) and Gemini CLI (~/.gemini/settings.json) share the same shape as Claude Desktop:
{
"mcpServers": { "spicyapi": { "command": "npx", "args": ["--yes", "--package=@spicyapi/mcp", "spicyapi-mcp"], "env": { "SPICY_API_KEY": "YOUR_SPICY_API_KEY" } } } }
On Windows these live under %USERPROFILE%. If a file already has other settings, merge mcpServers into it — the whole file must stay valid JSON, with no comments or trailing commas. Restart the client if the tools do not appear (Gemini CLI: /mcp lists them).
Those are user-level files outside your repository. Never copy that block, with a real key in it, into a project file that gets committed — such as a project-level .cursor/mcp.json.
.vscode/mcp.json is committed with your repository, so let VS Code prompt for the key and keep it in its own secret storage:
{
"inputs": [ { "id": "spicyapi-key", "type": "promptString", "description": "SpicyAPI key", "password": true } ], "servers": { "spicyapi": { "type": "stdio", "command": "npx", "args": ["--yes", "--package=@spicyapi/mcp", "spicyapi-mcp"], "env": { "SPICY_API_KEY": "${input:spicyapi-key}" } } } }
Start it from the code lens above the entry or MCP: List Servers, paste the key when asked, then use the tools from Chat in Agent mode.
Use the same command, args and env. Each client owns its config location and format, and both change between versions — their own documentation is authoritative.
Ask your assistant, in order:
spicyapi_service_status needs no key, so this proves the server starts.spicyapi_balance_get proves the key reaches the server.spicyapi_.None of these costs anything.
Use SpicyAPI to list the image models I can call, pick an inexpensive one, generate a cinematic
night portrait, and give me the result link when it finishes.
The agent reads the catalog, fetches the model's schema, obtains an exact quote and stops for your confirmation before anything is charged.
More prompts to try:
Model IDs always come from the live catalog. Any placeholder such as MODEL_ID_FROM_CATALOG in SpicyAPI documentation means an exact ID selected from that catalog, not a literal value.
| Tool | Purpose | Read-only | Billable | Confirmation |
|---|---|---|---|---|
spicyapi_service_status | Public health and readiness; no key needed | Yes | No | No |
spicyapi_docs_search | Search the bundled first-party documentation index; no key | Yes | No | No |
spicyapi_models_list | Enabled models and account-specific prices | Yes | No | No |
spicyapi_model_get | One model and its current input schema | Yes | No | No |
spicyapi_balance_get | Available, held and total balance | Yes | No | No |
spicyapi_usage_get | Settled USD usage for the current key | Yes | No | No |
spicyapi_tasks_list | One page of task metadata for the current key | Yes | No | No |
spicyapi_task_get | Read one task, including ready result links | Yes | No | No |
spicyapi_task_wait | Wait up to 300 seconds for a task to reach a terminal state | Yes | No | No |
spicyapi_task_quote | Price an exact request without creating anything | Yes | No | No |
spicyapi_upload_file | Read, upload and commit a local file; return its spicy:// URI | No | No | No |
spicyapi_download_url_create | Short-lived signed URL for a task output | No | No | No |
spicyapi_task_create | Create an asynchronous generation task | No | Yes | Always |
spicyapi_task_retry | Create a new task from a failed or expired one | No | Yes | Always |
spicyapi_task_purge | Destroy one terminal task's stored content (destructiveHint) | No | No | Always |
spicyapi_assets_list | One page of saved assets, each with its spicy://a/ reference | Yes | No | No |
spicyapi_assets_usage_get | Asset storage plan, what is stored, today's count, next plan | Yes | No | No |
spicyapi_asset_save | Save a task output, local file, URL or upload to the library | No | No | No |
spicyapi_asset_rename | Rename a saved asset; its reference stays the same | No | No | No |
spicyapi_asset_delete | Delete a saved asset for good (destructiveHint) | No | No | Always |
spicyapi_characters_list | One page of characters, each with its images in order | Yes | No | No |
spicyapi_character_get | One character with its images, as spicy://a/ references | Yes | No | No |
The server also registers two resources — `s
Solo se muestra el principio; lee el resto en el repo