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Cloud Translation API MCP Server

MCP Server generated by mcp.ag2.ai

Installation

Add the following to your MCP client configuration file.

Configuration

{
  "mcpServers": {
    "ag2-mcp-servers-cloud-translation-api": {
      "command": "python",
      "args": [
        "mcp_server/main.py",
        "stdio"
      ],
      "env": {
        "CONFIG": "{...}",
        "SECURITY": "YOUR_API_KEYS",
        "CONFIG_PATH": "path/to/mcp_config.json"
      }
    }
  }
}

You run an MCP Server that exposes a Model Context Protocol interface for the Google Translate v3beta1 API. This server lets you connect your MCP clients to a remote translation service through a consistent MCP workflow, enabling context-aware interactions with the translation API while keeping you in control of configuration and startup.

How to use

Start the MCP Server as a local process and connect your MCP client to it using the standard MCP transport you choose (stdio, SSE, or streamable HTTP). You interact with the server through the MCP client APIs supported by your workflow. The goal is to translate the OpenAPI-described translation capabilities into MCP endpoints that your tooling can consume, enabling model-context-aware translation tasks and related actions.

How to install

# Step 1: prerequisites
# Ensure you have Python 3.9+ installed
# Ensure you have pip and uv installed (uv is a development/run helper)

# Step 2: install dependencies
# If you are using a dev environment, run:
pip install -e ".[dev]"

# Alternative using the uv helper:
uv pip install --editable ".[dev]"

# Step 3: run the MCP server (stdio transport)
python mcp_server/main.py stdio

Configuration and starting the server

The server is started via a local Python command. You can customize startup with environment variables to point at your configuration, including the path to a JSON config, an inline JSON config string, and security settings.

{
  "type": "stdio",
  "name": "cloud_translate",
  "command": "python",
  "args": ["mcp_server/main.py", "stdio"],
  "env": [
    {"name": "CONFIG_PATH", "value": "path/to/mcp_config.json"},
    {"name": "CONFIG", "value": "{\"example\":true}"},
    {"name": "SECURITY", "value": "YOUR_API_KEYS_OR_TOKENS"}
  ]
}

Troubleshooting basics

If you encounter startup or transport issues, verify that the Python interpreter and dependencies are correctly installed, and that the server process has access to the specified configuration. Check any logs emitted by the server for hints about connectivity or parsing problems, and ensure your MCP client is configured to communicate with the same transport mode you started the server with.

Notes on usage and security

Keep security considerations in mind when enabling external access. If you expose the MCP server over HTTP, ensure you implement appropriate authentication and authorization controls and limit access to trusted clients. Store API keys and sensitive configuration in secure locations and avoid embedding secrets directly in code or configuration files.