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)
Image, video and audio generation APIs with USD quotes and confirmation before paid requests.
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。
SPICY_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 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"spicyapi-ai": {
"command": "npx",
"args": [
"-y",
"@spicyapi/mcp"
],
"env": {
"SPICY_API_KEY": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add spicyapi-ai --env SPICY_API_KEY=your-value -- npx -y @spicyapi/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": {
"spicyapi-ai": {
"command": "npx",
"args": [
"-y",
"@spicyapi/mcp"
],
"env": {
"SPICY_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": {
"spicyapi-ai": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@spicyapi/mcp"
],
"env": {
"SPICY_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。
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7日
注册名称已通过 GitHub 账户 spicyapi-ai 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:SPICY_API_KEY
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(0.6.2)于3天前进入注册中心。
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。
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
只显示了开头部分;其余内容请在仓库中阅读