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Cantonese.ai MCP Server

@hhy-joseph

代码仓库

基本信息

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其他

传输方式

stdio

作者

hhy-joseph

关于 Cantonese.ai MCP Server

暂无概览

#cantonese-ai#text-to-speech#speech-to-text

Cantonese.ai 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": {
    "cantonese-ai-mcp-server": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

Cantonese.ai 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 Cantonese.ai MCP Server?

An MCP (Model Context Protocol) server that provides tools for text-to-speech and speech-to-text conversion using the cantonese.ai API. It is designed for developers who need to integrate Cantonese or English audio processing into MCP‑compatible clients, such as LLM agents.

How to use Cantonese.ai MCP Server?

Install with uv, set the CANTONESE_AI_API_KEY environment variable, then run uv run mcp dev server.py for development or uv run server.py for use with Claude Desktop. Two tools are exposed: text_to_speech and speech_to_text.

Key features of Cantonese.ai MCP Server

  • Text‑to‑speech and speech‑to‑text via cantonese.ai API.
  • Supports Cantonese and English languages.
  • Secure API key handled as environment variable.
  • Modern tooling with uv for fast package management.
  • Easy integration with any MCP‑compatible client.

Use cases of Cantonese.ai MCP Server

  • Convert Cantonese text to audio for voice applications.
  • Transcribe Cantonese speech recordings into text.
  • Add English TTS capabilities to an MCP‑based agent.
  • Build interactive voice‑driven chatbots using MCP tools.
  • Automate audio file transcription in a development workflow.

常见问题

1

What tools does the server provide?

It provides `text_to_speech` to convert text into an audio file and `speech_to_text` to transcribe an audio file into text.

2

Which languages are supported?

The `text_to_speech` tool supports both Cantonese and English. The `speech_to_text` tool returns the detected language in its response.

3

How do I obtain and set my API key?

You need an API key from cantonese.ai. Export it as the environment variable `CANTONESE_AI_API_KEY` (e.g., in `.bashrc` or `.zshrc`).

4

What are the runtime requirements?

Python 3.8 or later and the `uv` package manager are required. Dependencies are managed with `uv sync` from `pyproject.toml`.

5

How can I run the server for development or with Claude Desktop?

For development, use `uv run mcp dev server.py`. For integration with Claude Desktop, run `uv run server.py` and configure the MCP connection.

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