Transcribe, summarize and analyze audio with AssemblyAI speech-to-text and Speech Understanding.
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com.assemblyai/mcp is an MCP server that transcribe, summarize and analyze audio with AssemblyAI speech-to-text and Speech Understanding. Its tool list has not been published yet over http, requires no API key, and scores 73/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients - only the file and path differ.
{
"mcpServers": {
"assemblyai": {
"url": "https://<host>/mcp",
"headers": {
"Authorization": "Bearer <ASSEMBLYAI_API_KEY>"
}
}
}
}Are you the author?
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Transcribe, summarize and analyze audio with AssemblyAI speech-to-text and Speech Understanding.
This server supports HTTP transport. Be the first to test it - help the community know if it works.
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Others in writing
Scrape, crawl, and map websites to Markdown or JSON via local CLI.
Create and edit PDFs: text, Markdown, tables, metadata and pages, with Japanese font embedding.
Any file → clean Markdown for AI agents: PDF, Office, EPUB, HTML, images, audio/video. Local MCP.
一键同步文章到多个内容平台,支持今日头条、WordPress、知乎、简书、掘金、CSDN、typecho各大平台,一次发布,多平台同步发布。解放个人生产力
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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 <ASSEMBLYAI_API_KEY>" }
}
}
}
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.