AutoGLM ASR MCP Server

MCP server for high-quality speech-to-text transcription using Zhipu AutoGLM ASR.

CN: 一个面向 Agent 的语音转文字 MCP 服务，支持长音频分块、上下文传递和时间戳分段。

For AI-oriented setup details, see AI_SETUP_GUIDE.md.

For AI Agents (TL;DR)

• Type: MCP Server
• Domain: ASR / speech-to-text / transcription
• Input: local audio file path
• Output: full transcript text + timestamp segments
• Best for: meeting notes, call analysis, subtitle draft, voice memo transcription
• Supported audio formats: mp3, wav, m4a, flac, ogg, webm
• Core tools: transcribe_audio, get_audio_info

What It Does

• Transcribes short and long audio files with automatic chunking.
• Uses context-aware modes to balance speed and quality.
• Returns readable full text and segment-level timestamps.
• Runs over stdio as an MCP server for coding assistants.

Tool Index

| Tool | Purpose | Required Args | Optional Args | Returns | |------|---------|---------------|---------------|---------| | transcribe_audio | Transcribe audio to text | audio_path | context_mode, max_concurrency | Full transcript and time-aligned segments | | get_audio_info | Inspect audio before transcription | audio_path | None | Duration, format, channels, sample rate, estimated chunks |

Features

• Fast long-audio transcription with sliding-window concurrency.
• Better accuracy through chunk-to-chunk context passing.
• Automatic splitting for long inputs (API limit friendly).
• Zero-install runtime with npx.
• Works with common MCP clients.

Installation

Prerequisites

ffmpeg must be installed:

# macOS
brew install ffmpeg

# Ubuntu/Debian
apt install ffmpeg

# Windows
choco install ffmpeg

Get your API key from Zhipu AI Open Platform.

NPX (Recommended)

npx autoglm-asr-mcp

Quick Start

Add this MCP server to your client config and set AUTOGLM_ASR_API_KEY.

{
  "mcpServers": {
    "autoglm-asr": {
      "command": "npx",
      "args": ["-y", "autoglm-asr-mcp"],
      "env": {
        "AUTOGLM_ASR_API_KEY": "your-api-key"
      }
    }
  }
}

Compatibility

• Claude Desktop / Claude Code
• Cursor
• Windsurf
• VS Code MCP
• Other MCP-compatible clients

VS Code quick install:

Tools

transcribe_audio

Transcribe an audio file into text with timing segments.

Arguments:

| Name | Type | Required | Description | |------|------|----------|-------------| | audio_path | string | Yes | Absolute path to the audio file | | context_mode | string | No | sliding (default), none (fastest), full_serial (best quality, slower) | | max_concurrency | integer | No | Max parallel requests, range 1-20, default 5 |

Returns:

• Full transcription text
• Timestamped segment list
• Basic run stats (chunks, mode, elapsed time)

Common errors:

• File not found or unreadable path
• Unsupported format or broken audio stream
• Missing/invalid API key

get_audio_info

Inspect an audio file before transcription.

Arguments:

| Name | Type | Required | Description | |------|------|----------|-------------| | audio_path | string | Yes | Absolute path to the audio file |

Returns:

• Duration
• Format
• Sample rate
• Channels
• Estimated chunks

Context Modes

| Mode | Speed | Quality | Description | |------|-------|---------|-------------| | sliding | Fast | High | First chunk initializes context, later chunks run in parallel with context | | none | Fastest | Medium | Chunks run independently in parallel | | full_serial | Slow | Best | All chunks transcribed sequentially with full context chain |

Environment Variables

| Variable | Default | Description | |----------|---------|-------------| | AUTOGLM_ASR_API_KEY | required | Your Zhipu API key | | AUTOGLM_ASR_API_BASE | https://open.bigmodel.cn/api/paas/v4/audio/transcriptions | API endpoint | | AUTOGLM_ASR_MODEL | glm-asr-2512 | ASR model name | | AUTOGLM_ASR_MAX_CHUNK_DURATION | 25 | Max chunk duration (seconds) | | AUTOGLM_ASR_MAX_CONCURRENCY | 5 | Default concurrency | | AUTOGLM_ASR_CONTEXT_MAX_CHARS | 2000 | Max context size passed between chunks |

Use Cases

• Meeting recording to editable transcript
• Customer support call transcription
• Podcast/video subtitle draft generation
• Voice memo indexing and search

Limitations

• Requires local file path input (not remote URL input).
• Audio quality strongly affects transcription quality.
• Very noisy or multi-speaker overlap can reduce accuracy.

Troubleshooting

• ffmpeg not found: install ffmpeg and retry.
• File not found: pass an absolute existing path.
• API errors: verify AUTOGLM_ASR_API_KEY and account quota.

Keywords

mcp, model-context-protocol, asr, speech-to-text, transcription, autoglm, zhipu, chinese-asr, audio-transcription, meeting-transcript, subtitle-generation, voice-to-text, agent-tools, llm-tools, coding-agent

License

MIT