Pascal 3D Editor
Create, inspect, validate, and save editable 3D building scenes with Pascal's MCP server.
Transcribe, summarize and analyze audio with AssemblyAI speech-to-text and Speech Understanding.
选择你使用的 AI 应用,然后复制设置。
通过 4/4 项检查 · 你的提问会经过开发者的服务器(mcp.assemblyai.com) · ✓ 命令已检查 2026年11月13日
第一步:你用哪个 AI?
选择你用的应用,步骤会显示在下方。
可连接 Claude · 约 2 分钟
不需要密钥,不用安装程序 · 在 claude.ai 或桌面应用设置一次,即可在聊天中使用 · 免费账户可添加 1 个 · Team/Enterprise 方案由所有者(Owner)添加
CustomizeConnectors
把这里的内容复制到 Claude 中同名的输入框,然后点击 Continue
AssemblyAIhttps://mcp.assemblyai.com/mcp在 Claude 检测到的登录设置页点击 Continue · Authentication 按作者说明选择(Sign in now、Sign in when needed 或 No sign in),然后点击 Add
+ConnectorsAssemblyAI
用 AssemblyAI 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude 说正在使用 AssemblyAI,或回答中出现 AssemblyAI 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
能否连接 ChatGPT 取决于方案
完整 MCP:网页版 ChatGPT Business、Enterprise 或 Edu · Pro:以读取/获取权限连接,修改数据的工具可能用不了 · Plus:官方文档尚未确认,如果在插件页看到添加自定义 MCP 的选项可以试试 · 仅限网页
Plugins+Add custom MCP server
输入名称,在 Connection 下粘贴地址,勾选风险提示,然后点击 Create as a plugin
AssemblyAIhttps://mcp.assemblyai.com/mcp开启新聊天,输入前先从插件列表中选择 AssemblyAI
用 AssemblyAI 告诉我你能帮我做什么,然后做一件给我看✓ 如果 ChatGPT 说正在使用 AssemblyAI,或回答中出现 AssemblyAI 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 OpenAI 帮助页面核实 · 你的界面可能因版本略有不同
可连接 Claude Code · 约 2 分钟
不需要密钥,不用安装程序
Mac:按 Command+空格,输入 Terminal · Windows:打开 PowerShell
claude mcp add --transport http --scope user assemblyai https://mcp.assemblyai.com/mcp应能看到 AssemblyAI 在列表中并显示已连接
用 AssemblyAI 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude Code 说正在使用 AssemblyAI,或回答中出现 AssemblyAI 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
可连接 Cursor · 约 2 分钟
不需要密钥,不用安装程序
用 AssemblyAI 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Cursor 说正在使用 AssemblyAI,或回答中出现 AssemblyAI 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Cursor 帮助页面核实 · 你的界面可能因版本略有不同
可连接 VS Code · 约 2 分钟
不需要密钥,不用安装程序
用 AssemblyAI 告诉我你能帮我做什么,然后做一件给我看✓ 如果 VS Code 说正在使用 AssemblyAI,或回答中出现 AssemblyAI 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 VS Code 帮助页面核实 · 你的界面可能因版本略有不同
其他支持 MCP 的应用(如 Windsurf、Zed、Gemini CLI)添加方式各不相同,请在应用列表中查看
通过网页连接的应用使用的地址
https://mcp.assemblyai.com/mcpJSON 设置在下方“开发者专用”中
Claude Code
claude mcp add --transport http --scope user assemblyai https://mcp.assemblyai.com/mcpCursor (~/.cursor/mcp.json)
{
"mcpServers": {
"assemblyai": {
"url": "https://mcp.assemblyai.com/mcp"
}
}
}VS Code (mcp.json)
{
"servers": {
"assemblyai": {
"type": "http",
"url": "https://mcp.assemblyai.com/mcp"
}
}
}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。
依据这个服务器的连接方式和各应用自己的文档,检查于 2026年11月10日。
通过互联网连接,适用于
ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast
服务器要求先登录,才会列出它的工具。
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15日
注册名称已通过域名 assemblyai.com 验证(注册中心会核实域名所有权)
代码最后更新于昨天
不适用:由 assemblyai.com 的所有者自己运行的云端服务器,你不会运行仓库里的代码
在 194 毫秒内响应(HTTP 401)
声明支持 OAuth 登录,你的 AI 应用可以带你去登录
尚未检查;我们会在检查端点时读取工具列表
提问、分享技巧或报告无法使用。按“有帮助”数量排序。
还没有评价
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 4 项适用的基础检查中通过了 4 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。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于昨天,最新版本(1.0.0)于11天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,因此也能用于接受远程 MCP 的应用,例如网页版 ChatGPT(Business 及以上为完整 MCP;Pro 为只读)。
同一分类中有:Pascal 3D Editor, Figma MCP Server, Remocn: Remotion MCP server, Harness, ChatCut
同一分类、其他作者、命令已通过检查。官方的排在前面,再按星标排序。
如何看卡片:↓ 每周下载量i★ 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
Create, inspect, validate, and save editable 3D building scenes with Pascal's MCP server.
The Figma MCP server brings Figma design context directly into your AI workflow.
Hosted MCP for Remotion videos: search Remocn components, read docs, plan a video, preview it.
Start Claude Code and Codex agents the person can watch, wait for them and read their answers.
AI video editor for agents: cut footage, add captions and motion graphics, export editable edits.
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。
A remote MCP server for the AssemblyAI API. It gives any MCP-capable agent five tools covering async speech-to-text, Speech Understanding (translation, speaker identification, custom formatting, chaptered summarization, action items), and Guardrails (PII redaction, content moderation, profanity filtering) — served over Streamable HTTP and authenticated per-request, either by signing in with AssemblyAI (OAuth) or with the caller's own AssemblyAI API key.
Works with any MCP client that supports MCP authorization (Claude Code, Claude.ai, Cursor, MCP Inspector, and others) or can send a Bearer header. Built with Next.js 16 + mcp-handler + the official @modelcontextprotocol/sdk; deploys as a Vercel serverless function.
AssemblyAI hosts it at `https://mcp.assemblyai.com/mcp`. It's listed in the official MCP Registry as com.assemblyai/mcp. Setup for Claude, Cursor, VS Code and other clients: assemblyai.com/docs/mcp-server.
Sign in with AssemblyAI: add the server's /mcp endpoint with no headers. The client opens AssemblyAI's sign-in and consent page, and the server uses an API key it gets for that connection; nothing to copy or paste. (This works against AssemblyAI's hosted deployment; a self-hosted copy uses API keys, see Auth.)
claude mcp add --transport http assemblyai https://mcp.assemblyai.com/mcp
With an API key: point your MCP client at the /mcp endpoint with your AssemblyAI API key as the Bearer token.
Claude Code
claude mcp add --transport http assemblyai https://mcp.assemblyai.com/mcp \
--header "Authorization: Bearer $ASSEMBLYAI_API_KEY"
Generic remote-MCP client config
{
"mcpServers": { "assemblyai": { "url": "https://mcp.assemblyai.com/mcp", "headers": { "Authorization": "Bearer " } } } }
Running your own copy? npm install && npm run dev serves it at http://localhost:3000/mcp (see Local dev).
Then prompt the agent, e.g. *"transcribe this audio file and summarize it: https://assembly.ai/wildfires.mp3"*.
| Tool | Purpose | |
|---|---|---|
| `submit_transcript(audio_url \ | file, ...)` | Start an async transcription of a public audio/video URL (audio_url). In ChatGPT only, a file the user attached can go in file instead (ChatGPT fills it in through _meta["openai/fileParams"]; other clients ignore it). Returns { transcript_id, status } immediately. |
get_transcript(transcript_id, include_words?) | Fetch the current state; full results once status is completed. Agents poll this ~every 3s. Per-word timestamps only with include_words: true. | |
understand_transcript(transcript_id, speech_understanding) | Run Speech Understanding on an already-completed transcript — translation, speaker identification, custom formatting, chaptered summarization, action items — without re-submitting the audio (LLM Gateway /v1/understanding). | |
summarize_transcript(transcript_id, style?, custom_prompt?) | Freeform or custom-prompt summary of a completed transcript via the LLM Gateway. style: bullets (default), paragraph, headline, action_items, or custom. | |
delete_transcript(transcript_id) | Permanently delete a transcript and its data. Irreversible — only on explicit user request. | |
create_upload_url() | For a local file: returns a 10-minute link and a curl command. The agent uploads the file (up to 4.5 MB) and gets an upload_url to pass to submit_transcript. Only offered when UPLOAD_TOKEN_SECRET is set. |
Typical agent flow: submit_transcript → poll get_transcript until completed → optionally understand_transcript / summarize_transcript → delete_transcript when the user asks for cleanup. When the need is known up front, request Speech Understanding features inline at submit time instead of post-hoc.
submit_transcript parameter surfaceAccepts the full public async transcription param surface with API-native names, grouped roughly as:
prompt (a contextual *description* of the audio, not instructions), keyterms_promptlanguage_code, language_codes, language_detection, language_detection_options, language_confidence_thresholdspeech_models (defaults to the pinned ["universal-3-5-pro", "universal-2"] priority list), temperaturespeaker_labels, speaker_optionsredact_pii (+ redact_pii_policies, redact_pii_sub, redact_pii_audio, redact_pii_return_unredacted, redact_static_entities), filter_profanity, content_safety (+ content_safety_confidence), speech_thresholdspeech_understanding.request.{translation, speaker_identification, custom_formatting, summarization, action_items}, run during transcriptionsentiment_analysis (English only), entity_detection, iab_categories, auto_highlights, multichannel, disfluencies, custom_spelling, punctuate, format_text, audio_start_from, audio_end_at, domain (medical-v1 for Medical Mode), and remove_audio_tags, plus webhooks (webhook_url, webhook_auth_header_name/_value)Omitted params are never sent — AssemblyAI's own defaults apply. See the submit endpoint docs for parameter semantics.
get_transcript outputEverything renders into content[].text as labeled sections, because some MCP clients surface only that to the model: --- text --- and --- utterances --- always; sentiment, entities, translations (whole-transcript and per-utterance), speaker identification, custom formatting, chaptered summary, action items, content safety, topics, highlights, unredacted text, the redacted-audio URL, and processing warnings when requested/present. Raw fields are mirrored in structuredContent.
Every request carries a Bearer token, which is one of two things.
An OAuth access token (Sign in with AssemblyAI). A request with no token gets a 401 whose WWW-Authenticate names /.well-known/oauth-protected-resource, which names AssemblyAI's authorization server. The client registers itself there, signs the member in through the consent page (scope aai:api), and sends the access token it gets back. AssemblyAI's API takes API keys, not access tokens, so src/oauth.ts exchanges the token for the API key of the member's connection to that client (POST /api/v2/oauth/api-key) before the request reaches withMcpAuth, and the request continues with that key. The exchange also proves which server is asking: the deployment's Vercel OIDC token goes in X-AAI-Service-Token, and AssemblyAI only accepts its own production deployment of this project, so a self-hosted copy can't exchange tokens and uses API keys instead. Keys are cached per access token for at most five minutes, so a connection revoked from the dashboard stops working within minutes. A refused token answers 401 (403 for a missing scope) and sends the client back to sign-in; an outage answers 503, which doesn't.
An AssemblyAI API key (pass-through). MCP clients send the API key as Authorization: Bearer (most client configs prepend Bearer automatically). AssemblyAI's REST API expects the raw key, so withMcpAuth extracts the token, strips the prefix, and threads it into every tool callback via extra.authInfo.token. No keys are written to disk or shared between requests — each request runs on the key it arrived with.
Every setting defaults to AssemblyAI's production endpoints, so a production deployment needs none. A deployment that signs in against another AssemblyAI environment sets all four together, since that environment's keys only work against its own API.
| Variable | Default | What it is |
|---|---|---|
ASSEMBLYAI_OAUTH_ISSUER | https://auth.assemblyai.com | The authorization server advertised in the protected resource metadata |
ASSEMBLYAI_OAUTH_EXCHANGE_ORIGIN | https://www.assemblyai.com | Where access tokens are exchanged for API keys |
ASSEMBLYAI_BASE_URL | https://api.assemblyai.com | The AssemblyAI API |
ASSEMBLYAI_LLM_GATEWAY_BASE_URL | https://llm-gateway.assemblyai.com | The LLM Gateway |
UPLOAD_TOKEN_SECRET | unset | 32+ random characters. Encrypts the API key inside upload links; without it, create_upload_url is not offered. Rotating it invalidates open links. |
The service token needs no setting: Vercel provides it to the deployment (VERCEL_OIDC_TOKEN), and @vercel/oidc reads it.
MCP clients discover tools at runtime (list_tools); client configs store only URL + auth, not a tool-schema snapshot. So new tools and new optional parameters appear automatically — no client reconfiguration, and for platforms with a connection-test step, no re-test. To keep that guarantee, all changes here are additive:
get_transcript text output only *gains* labeled sections** — existing sections (--- text ---, --- utterances ---, --- sentiment ---, --- entities ---) are never renamed or reshaped, because text-only MCP clients read content[].text. (A legacy --- summary --- section is still rendered if present, but summaries now come from the summarize_transcript tool, not get_transcript.) The same protection covers the newer sections added for Speech Understanding and guardrails: --- translation: ---, --- translated_utterances ---, --- speaker_identification ---, --- custom_formatting ---, --- su_summary ---, --- action_items ---, --- content_safety ---, --- topics ---, --- highlights ---, --- unredacted_text ---, --- redacted_audio ---, and --- warnings ---.speakers[].words) were never part of the declared shape and made up ~85% of every response, so they now come back only with include_words: true.auto_chapters, summarization, summary_model, summary_type); use LLM Gateway instead. Mirror AssemblyAI's official MCP tool shapes where they exist.Requires Node 24.x.
npm install
npm test # in-process smoke + OAuth exchange tests (no network) npm run dev # next dev on http://localhost:3000
MCP endpoint: http://localhost:3000/mcp. OAuth protected resource metadata: http://localhost:3000/.well-known/oauth-protected-resource. Sign-in needs a deployment AssemblyAI accepts (see Auth); locally, use an API key.
npx @modelcontextprotocol/inspector
Connect to http://localhost:3000/mcp via Streamable HTTP, paste your AssemblyAI key as the Bearer token. Call submit_transcript with a public mp3 URL, then get_transcript with the returned id until completed.
# No auth — expect 401
curl -i -X POST http://localhost:3000/mcp \ -H "Accept: application/json, text/event-stream" \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"curl","version":"1"}}}'
curl -i -X POST http://localhost:3000/mcp \ -H "Author