
AssemblyAI
com.assemblyai由 assemblyai.com 發布官方發布者v1.0.0更新於 Nov 3, 2026
使用 AssemblyAI 語音轉文字和 Speech Understanding 轉寫、總結並分析音訊。
AI 翻譯由 AI 模型根據下方的原文描述翻譯,可能有誤。
原文描述
Transcribe, summarize and analyze audio with AssemblyAI speech-to-text and Speech Understanding.
概覽
AssemblyAI 的託管 MCP 服務(mcp.assemblyai.com),由 assemblyai.com 發布;需要 OAuth 登入;Streamable HTTP。
暫無 AI 概覽:以下資訊來自註冊中心條目和服務本身。
- 發布者
- assemblyai.com
- 端點
- mcp.assemblyai.com
- 最近檢查
安裝
在 SourceWeft 中
- 開啟 儀表板中的 AssemblyAI,將其新增到工作區。
- 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
- 為需要使用其工具的對話啟用該服務。
Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。
交給代理程式安裝
把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。
閱讀 https://sourceweft.com/mcp/com.assemblyai%2Fmcp/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。其他 MCP 客戶端
把它新增到你客戶端的 mcpServers 設定中。 客戶端會在首次連接時完成 OAuth 登入。
{
"mcpServers": {
"assemblyai": {
"type": "http",
"url": "https://mcp.assemblyai.com/mcp"
}
}
}README
AssemblyAI MCP Server
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.
Quickstart
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.)
With an API key: point your MCP client at the /mcp endpoint with your
AssemblyAI API key as the Bearer token.
Claude Code
Generic remote-MCP client config
No hosted instance handy? 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".
Tools
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 surface
Accepts the full public async transcription param surface with API-native names, grouped roughly as:
- Prompting —
prompt(a contextual description of the audio, not instructions),keyterms_prompt - Language —
language_code,language_codes,language_detection,language_detection_options,language_confidence_threshold - Models —
speech_models(defaults to the pinned["universal-3-5-pro", "universal-2"]priority list),temperature - Diarization —
speaker_labels,speaker_options - Guardrails —
redact_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_threshold - Speech Understanding, inline —
speech_understanding.request.{translation, speaker_identification, custom_formatting, summarization, action_items}, run during transcription - Other —
sentiment_analysis(English only),entity_detection,iab_categories,auto_highlights,multichannel,disfluencies,custom_spelling,punctuate,format_text,audio_start_from,audio_end_at,domain(medical-v1for Medical Mode), andremove_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 output
Everything 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.
Auth
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 <key> (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.
Configuration
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.
The service token needs no setting: Vercel provides it to the deployment
(VERCEL_OIDC_TOKEN), and @vercel/oidc reads it.
Extending the tool surface (additive-only contract)
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:
- Tool names are permanent — only add tools, never rename or remove.
- New inputs are always optional, with defaults that preserve current behavior.
get_transcripttext output only gains labeled sections — existing sections (--- text ---,--- utterances ---,--- sentiment ---,--- entities ---) are never renamed or reshaped, because text-only MCP clients readcontent[].text. (A legacy--- summary ---section is still rendered if present, but summaries now come from thesummarize_transcripttool, notget_transcript.) The same protection covers the newer sections added for Speech Understanding and guardrails:--- translation:<lang> ---,--- translated_utterances ---,--- speaker_identification ---,--- custom_formatting ---,--- su_summary ---,--- action_items ---,--- content_safety ---,--- topics ---,--- highlights ---,--- unredacted_text ---,--- redacted_audio ---, and--- warnings ---.structuredContentis additive only — new fields, never removed/renamed.- Avoid deprecated AssemblyAI transcript params (
auto_chapters,summarization,summary_model,summary_type); use LLM Gateway instead. Mirror AssemblyAI's official MCP tool shapes where they exist.
Local dev
Requires Node 24.x.
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.
Smoke test with MCP 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.
Smoke test with curl
Live end-to-end test (real AssemblyAI, real transcription)
Drives the running server with the MCP SDK client over Streamable HTTP:
tool discovery, all submit_transcript feature flags, speech_model_used
assertion, summarize_transcript, inline Speech Understanding (translation +
chaptered summary), guardrails (content safety), post-hoc Speech
Understanding via understand_transcript, graceful failure on a bad audio
URL, and teardown via delete_transcript. Every transcript id is recorded
as soon as submit_transcript returns it and deleted from a finally
block, so the suite tears down every transcript it successfully creates
even when the run fails midway. Costs a few cents of transcription credit
per run.
Sign-in test against a deployment
Signs in the way an MCP client does, discovering everything from the
deployment: the 401 challenge, the protected resource metadata, the
authorization server's metadata, client registration, then PKCE through the
consent page in your browser (click Allow). Then it lists tools and makes one
tool call with the access token, and checks a tampered token is refused.
VERCEL_PROTECTION_BYPASS is the deployment's Protection Bypass for
Automation secret, for preview deployments behind Vercel Authentication.
No API key needed and no transcription credit spent.
Project layout
Logging
JSON to stdout, same pattern as AssemblyAI's docs MCP server. Every tool
emits one event with event, tool, keyHash, latencyMs, status.
High-signal events worth alerting on: bad_audio_url,
assemblyai_rejected_key, tool_error, understanding_error,
delete_error. Never logs the raw API key — only sha256(key).slice(0,12)
— and never logs transcript content.
Deployment
Deploys to Vercel (vercel deploy once the project is linked). Vercel
Firewall provides rate limiting and DDoS protection. The MCP endpoint lives
at https://<host>/mcp with maxDuration: 60 per the handler config.
Reference: prior Python implementation
The Python FastMCP-based implementation that preceded this TypeScript
port is preserved in the first commit of this repo
(git log --reverse --oneline | head -1). It serves as the source of
truth for the design (auth bridge, error handling, response shapes); this
TypeScript port carries the design forward onto a serverless-friendly
platform.
來源:README.md,提交 cb71979
工具
0版本歷史
1- v1.0.0最新Nov 3, 2026
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