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)
Transcribe local files and URLs with SpeechWeave's OpenAI-compatible Speech-to-Text API.
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。
SPEECHWEAVE_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": {
"speechweave": {
"command": "npx",
"args": [
"-y",
"@speechweave/mcp"
],
"env": {
"SPEECHWEAVE_API_KEY": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add speechweave --env SPEECHWEAVE_API_KEY=your-value -- npx -y @speechweave/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": {
"speechweave": {
"command": "npx",
"args": [
"-y",
"@speechweave/mcp"
],
"env": {
"SPEECHWEAVE_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": {
"speechweave": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@speechweave/mcp"
],
"env": {
"SPEECHWEAVE_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6日
注册名称已通过 GitHub 账户 speechweave 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:SPEECHWEAVE_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(1.10.0)于16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。
Official Model Context Protocol server for SpeechWeave. Use to transcribe local files and URLs from Cursor, Claude Desktop, Claude Code, Windsurf, and other MCP clients.
SpeechWeave handles short clips and long-form audio without client-side chunking. This MCP server exposes both sync tools (the transcript comes back in the same tool call) and async tools (start a job, then poll for status).
Docs: speechweave.com/docs/mcp · API reference
Requires Node.js 18+ and a SpeechWeave API key (sk_live_…).
export SPEECHWEAVE_API_KEY="sk_live_..."
npx -y @speechweave/mcp
Add to your MCP config (e.g. .cursor/mcp.json, claude_desktop_config.json):
{
"mcpServers": { "speechweave": { "command": "npx", "args": ["-y", "@speechweave/mcp"], "env": { "SPEECHWEAVE_API_KEY": "sk_live_..." } } } }
claude mcp add speechweave --env SPEECHWEAVE_API_KEY=sk_live_... -- npx -y @speechweave/mcp
| Tool | Delivery | When to use |
|---|---|---|
transcribe_file | sync | Absolute local path. Returns the transcript in this call |
transcribe_url | sync | Public HTTPS URL. Returns the transcript in this call |
start_job_file | async | Absolute local path. Returns job_id immediately |
start_job_url | async | Public HTTPS URL. Returns job_id immediately |
get_job_status | async | Poll status / transcript for a job id |
cancel_job | n/a | Cancel a queued or processing job |
get_limits | n/a | Upload size ceilings for your API key |
fetch_doc | n/a | Public docs by slug (bundled pages + live OpenAPI) |
Delivery (sync or async) is separate from service_mode (standard or deferred). Either service mode works with either delivery.
Never pass raw audio bytes over MCP. Use absolute file paths (local clients) or HTTPS URLs.
All transcription and job-start tools accept the following optional arguments:
model: Choose core (default) or max.service_mode: Choose standard (default) or deferred (lower cost, lower priority).language: Optional ISO language code to force language detection.task: Choose transcribe (default) or translate to produce an English translation instead. language is ignored when translating.prompt: Optional custom vocabulary hint (proper nouns, acronyms, product names) for the first ~30s of audio.Formatted transcripts: transcribe_file, transcribe_url, and get_job_status also accept an optional response_format (text, srt, vtt, or verbose_json) to return the transcript in that shape instead of the default plain text.
Saving to a file: transcribe_file, transcribe_url, and get_job_status accept output_file (an absolute path). The transcript is written there instead of being returned, so long transcripts stay out of the conversation. The result includes output_file and bytes_written. The path must end in .txt, .md, .json, .srt, or .vtt and cannot be inside a hidden folder. The parent folder must exist, and an existing file is only replaced when overwrite is true. With response_format: "verbose_json" the file holds the text plus segment timings as JSON.
Billing errors: a 402 comes back as a tool error with code and a hint. USER_SPEND_CAP_REACHED (raise your spend cap), PLATFORM_SPEND_CAP_REACHED (monthly account limit, request an increase), and INSUFFICIENT_BALANCE or WALLET_EMPTY (top up) all need a change on the account first, so the hint tells the assistant not to retry.
Timeout behavior: Sync tools accept an optional timeout_ms. If the transcription exceeds the timeout, the tool gracefully returns a job_id and instructs the client to switch to get_job_status polling.
get_limits: Returns GET /v1/limits for the calling key, with MB equivalents. Use before uploading large local files.fetch_doc: Returns public documentation. Slug list shows the catalog. Bundled pages include quickstart, mcp, models, billing, and data_retention. Slug api fetches a live OpenAPI overview, and api/ returns one endpoint (e.g. api/get_v1_limits).After adding the server and restarting your client, try asking your AI assistant:
"Use SpeechWeave to transcribe
/Users/me/recordings/standup.mp3and summarize action items."
*The assistant will call transcribe_file with the absolute path and summarize the returned transcript.*
"Start a SpeechWeave job for
https://cdn.example.com/three_hour_podcast.mp3, then check back until it completes."
*The assistant will call start_job_url, then periodically call get_job_status until the status reaches completed.*
"Translate
/Users/me/recordings/spanish_interview.mp3into English SRT subtitles using SpeechWeave."
*The assistant will call transcribe_file with task: "translate" and response_format: "srt".*