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FunASR-Powered MCP Server (MCPServer)

@radial-hks

リポジトリ

基本情報

カテゴリ

開発者ツール

ライセンス

MIT license

トランスポート

stdio

作者

radial-hks

FunASR-Powered MCP Server について

MCPServer is a Python-based server that leverages Alibaba's FunASR library to provide speech processing services through the FastMCP framework.

#mcp-server#speech-processing#funasr

FunASR-Powered MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp-server-funasr": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        ".venv"
      ]
    }
  }
}

FunASR-Powered MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is FunASR-Powered MCP Server (MCPServer)?

MCPServer is a Python-based server that leverages Alibaba's FunASR library to provide speech processing services through the FastMCP framework. It offers tools for audio validation, asynchronous speech transcription with models like Paraformer, and voice activity detection (VAD). It is designed for developers integrating speech capabilities into MCP-compatible applications.

How to use FunASR-Powered MCP Server (MCPServer)?

Install dependencies with pip install -r requirements.txt, then run the server using uvicorn main:app --host 0.0.0.0 --port 9000. Interact via any MCP client; the server exposes tools at http://0.0.0.0:9000/sse. Optionally set MODELSCOPE_API_TOKEN for model downloads.

Key features of FunASR-Powered MCP Server (MCPServer)

  • Audio file validation (format, duration, sample rate).
  • Asynchronous speech-to-text transcription with task management.
  • Detailed transcription results including segment and word timestamps.
  • Voice activity detection returning precise speech segment timestamps.
  • Dynamic loading and switching of ASR and VAD models.
  • Configurable model parameters per request.

Use cases of FunASR-Powered MCP Server (MCPServer)

  • Transcribing long audio recordings (meetings, lectures) asynchronously.
  • Validating audio file integrity before further processing.
  • Detecting speech segments in audio for speaker diarization or silence removal.
  • Building custom voice‑based applications with flexible model selection.

よくある質問

1

What are the runtime requirements?

Python 3.8 or higher and pip. FunASR downloads models from ModelScope; a `MODELSCOPE_API_TOKEN` may be needed to avoid rate limits or access private models.

2

How does transcription work?

Transcription tasks are fully asynchronous – submit a job, poll its status, and retrieve the result when completed. Results include full text, segment timestamps, and word‑level timestamps where available.

3

Can I use different ASR or VAD models?

Yes. You can specify a model per request (e.g., via `model_name` parameter) or load a new default model using `load_asr_model` or `load_vad_model` tools.

4

Where are audio files processed?

Audio files are processed on the server from local file paths. The server does not store or stream audio externally; all processing occurs in‑memory.

5

What transport and authentication does the server use?

The server uses SSE (Server‑Sent Events) at the `/sse` endpoint. No authentication is described in the README.

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