What actions does MCP Gemini Server support?
It supports three actions: `generate_text`, `analyze_text`, and `chat`.
@amitsh06
Basic information
No overview available yet
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-server-amitsh06": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
MCP Gemini Server is an implementation of the Model Context Protocol (MCP) that enables AI assistants like Claude to interact with Google's Gemini API. It allows AI assistants to request text generation, text analysis, and maintain chat conversations through the Gemini API.
Install Python 3.7+ and obtain a Google AI API key. Clone the repository, create a virtual environment, install dependencies, and set your API key in a .env file as GEMINI_API_KEY. Start the server with python server.py, then send POST requests to the /mcp endpoint with a JSON payload containing the action and parameters.
It supports three actions: `generate_text`, `analyze_text`, and `chat`.
You must provide a `prompt`. Optional parameters include `temperature` (0.0 to 1.0) and `max_tokens`.
The `analysis_type` parameter can be `'sentiment'`, `'summary'`, `'keywords'`, or `'general'`.
Run `python server.py` after installing dependencies and setting your `GEMINI_API_KEY` in a `.env` file.
It exposes `GET /health`, `GET /list-models`, and `POST /mcp` as the main endpoint for MCP requests.

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