Whissle MCP Server
A Python-based server that provides access to Whissle API endpoints for speech-to-text, diarization, translation, and text summarization.
⚠️ Important Notes
- This server provides access to Whissle API endpoints which may incur costs
- Each tool that makes an API call is marked with a cost warning
- Please follow these guidelines:
- Only use tools when explicitly requested by the user
- For tools that process audio, consider the length of the audio as it affects costs
- Some operations like translation or summarization may have higher costs
- Tools without cost warnings in their description are free to use as they only read existing data
Prerequisites
- Python 3.8 or higher
- pip (Python package installer)
- A Whissle API authentication token
Installation
- Clone the repository:
- Create and activate a virtual environment:
- Install the required packages:
- Set up environment variables:
Create a
.env
file in the project root with the following content:⚠️ Important: Never commit your actual token to the repository. The.env
file is included in.gitignore
to prevent accidental commits. - Configure Claude Integration:
Copy
claude_config.example.json
toclaude_config.json
and update the paths:- Replace
/path/to/your/venv/bin/python
with the actual path to your Python interpreter in the virtual environment - Replace
/path/to/whissle_mcp/server.py
with the actual path to your server.py file
- Replace
Configuration
Environment Variables
WHISSLE_AUTH_TOKEN
: Your Whissle API authentication token (required)- This is a sensitive credential that should never be shared or committed to version control
- Contact your administrator to obtain a valid token
- Store it securely in your local
.env
file
WHISSLE_MCP_BASE_PATH
: Base directory for file operations (optional, defaults to user's Desktop)
Supported Audio Formats
The server supports the following audio formats:
- WAV (.wav)
- MP3 (.mp3)
- OGG (.ogg)
- FLAC (.flac)
- M4A (.m4a)
File Size Limits
- Maximum file size: 25 MB
- Files larger than this limit will be rejected
Available Tools
1. Speech to Text
Convert speech to text using the Whissle API.
2. Speech Diarization
Convert speech to text with speaker identification.
3. Text Translation
Translate text from one language to another.
4. Text Summarization
Summarize text using an LLM model.
5. List ASR Models
List all available ASR models and their capabilities.
Response Format
Speech to Text and Diarization
Translation
Summarization
Error Response
Error Handling
The server includes robust error handling with:
- Automatic retries for HTTP 500 errors
- Detailed error messages for different failure scenarios
- File validation (existence, size, format)
- Authentication checks
Common error types:
- HTTP 500: Server error (with retry mechanism)
- HTTP 413: File too large
- HTTP 415: Unsupported file format
- HTTP 401/403: Authentication error
Running the Server
- Start the server:
- The server will be available at the default MCP port (usually 8000)
Testing
A test script is provided to verify the functionality of all tools:
The test script will:
- Check for authentication token
- Test all available tools
- Provide detailed output of each operation
- Handle errors gracefully
Support
For issues or questions, please:
- Check the error messages for specific details
- Verify your authentication token
- Ensure your audio files meet the requirements
- Contact Whissle support for API-related issues
License
[Add your license information here]
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
음성-텍스트 변환, 일기, 번역, 텍스트 요약을 위한 Whissle API 엔드포인트에 대한 액세스를 제공하는 Python 기반 서버입니다.
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