Skip to main content
Glama

MCP Audio Transcriber

MCP 音频转录器

一个 Dockerized Python 工具,通过 AssemblyAI 的 API 实现模型上下文协议 (MCP)。上传或指向音频文件,即可接收结构化的 JSON 转录。

特征

  • AssemblyMCP :使用 AssemblyAI 的 REST API 的具体 MCP 实现

  • 命令行界面app.py ):

    python app.py <input_audio> <output_json>
  • Streamlit 网页用户界面( streamlit_app.py ):

    • 上传本地文件或粘贴 URL

    • 点击转录

    • 预览成绩单并下载 JSON

  • Docker 对环境一致性和可移植性的支持

先决条件

  • Python 3.10+

  • AssemblyAI API 密钥

  • ffmpeg(用于本地解码,如果使用本地文件)

  • (可选)Docker 桌面/引擎

  • (可选)Streamlit( pip install streamlit

🔧 安装

  1. 克隆 repo

    git clone https://github.com/ShreyasTembhare/MCP---Audio-Transcriber.git cd MCP---Audio-Transcriber
  2. 创建.env

    ASSEMBLYAI_API_KEY=your_assemblyai_api_key_here
  3. 确保.gitignore包含:

    .env
  4. 安装 Python 依赖项

    pip install --upgrade pip pip install -r requirements.txt
  5. 安装 ffmpeg

    • Ubuntu/Debian: sudo apt update && sudo apt install ffmpeg -y

    • Windows:从https://ffmpeg.org下载并将其bin/添加到您的 PATH

用法

1. CLI 转录

python app.py <input_audio> <output_json>
  • <input_audio> :AssemblyAI 支持的任何文件或 URL

  • <output_json> :生成的 JSON 的路径

例子:

python app.py data/input.ogg data/output.json cat data/output.json

2. Streamlit Web UI

streamlit run streamlit_app.py

3. Docker

构建图像:

docker build -t mcp-transcriber .

运行它(挂载你的数据/文件夹):

docker run --rm \ -e ASSEMBLYAI_API_KEY="$ASSEMBLYAI_API_KEY" \ -v "$(pwd)/data:/data" \ mcp-transcriber:latest \ /data/input.ogg /data/output.json

然后检查:

ls data/output.json cat data/output.json

Windows PowerShell:

docker run --rm ` -e ASSEMBLYAI_API_KEY=$env:ASSEMBLYAI_API_KEY ` -v "${PWD}\data:/data" ` mcp-transcriber:latest ` /data/input.ogg /data/output.json

项目结构

MCP-Audio-Transcriber/ ├── app.py # CLI entrypoint (AssemblyMCP only) ├── mcp.py # ModelContextProtocol + AssemblyMCP ├── streamlit_app.py # Streamlit interface ├── requirements.txt # assemblyai, python-dotenv, streamlit, etc. ├── Dockerfile # builds the container ├── .gitignore # ignores .env, __pycache__, etc. ├── LICENSE # MIT license └── data/ # sample input and output ├── input.ogg └── output.json
-
security - not tested
A
license - permissive license
-
quality - not tested

local-only server

The server can only run on the client's local machine because it depends on local resources.

一种可移植的 Dockerized Python 工具,使用 Whisper 模型实现用于音频转录的模型上下文协议,具有 CLI 和 Web UI 界面,用于将音频文件转换为 JSON 转录。

  1. 特征
    1. 先决条件
      1. 🔧 安装
        1. 用法
          1. 1. CLI 转录
          2. 2. Streamlit Web UI
          3. 3. Docker
        2. 项目结构

          Related MCP Servers

          • -
            security
            A
            license
            -
            quality
            Enables recording audio from a microphone and transcribing it using OpenAI's Whisper model. Works as both a standalone MCP server and a Goose AI agent extension.
            Last updated -
            6
            MIT License
          • -
            security
            F
            license
            -
            quality
            A Model Context Protocol server that provides AI-powered features for the Transcripter project, including tools for searching and summarizing transcriptions and resources for accessing transcription and analysis data.
          • -
            security
            F
            license
            -
            quality
            Enables seamless integration with Typecast API through the Model Context Protocol, allowing clients to manage voices, convert text to speech, and play audio in a standardized way.
            Last updated -
            2
          • Gladia MCPofficial

            -
            security
            A
            license
            -
            quality
            Official Model Context Protocol server that enables interaction with powerful Speech-to-Text and Audio Intelligence APIs, allowing clients like Claude Desktop to transcribe audio, analyze speech, translate content, and more.

          View all related MCP servers

          MCP directory API

          We provide all the information about MCP servers via our MCP API.

          curl -X GET 'https://glama.ai/api/mcp/v1/servers/ShreyasTembhare/MCP---Audio-Transcriber'

          If you have feedback or need assistance with the MCP directory API, please join our Discord server