FunASR-Powered MCP Server (MCPServer)

@radial-hks

代码仓库

基本信息

分类

开发工具

许可证

MIT license

传输方式

stdio

作者

radial-hks

关于 FunASR-Powered MCP Server

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 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

FunASR-Powered MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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.

常见问题

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.

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.

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.

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.

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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