What runtime is required?
Node.js version 18 or later.
@MCP-Mirror
Basic information
Mirror of
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"bsmi021_mcp-gemini-server": {
"command": "npx",
"args": [
"-y",
"@smithery/cli",
"install",
"@bsmi021/mcp-gemini-server",
"--client",
"claude"
]
}
}
}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.
Fetch the live tool list by running this server in a temporary sandbox using the button above.
This server wraps the @google/genai SDK, exposing Google Gemini model capabilities as standard MCP tools. It allows other LLMs (like Cline) or MCP-compatible systems to leverage Gemini’s text generation, function calling, chat, file handling, and caching features.
Install via Smithery (npx -y @smithery/cli install @bsmi021/mcp-gemini-server) or manually (clone, npm install, npm run build). Configure your MCP client’s settings with the server’s path and required environment variables (GOOGLE_GEMINI_API_KEY, optionally GOOGLE_GEMINI_MODEL). Restart the client after configuration.
gemini_generateContent, gemini_generateContentStream)Node.js version 18 or later.
An API key from Google AI Studio ([https://aistudio.google.com/app/apikey](https://aistudio.google.com/app/apikey)).
No. The server only supports Google AI Studio API keys; file handling and caching features are not compatible with Vertex AI credentials.
Set the `GOOGLE_GEMINI_MODEL` environment variable (e.g., `gemini-1.5-flash`). If not set, the `modelName` parameter becomes required on applicable tool calls.
Errors are returned as `McpError` objects with an error code (`InvalidParams`, `InternalError`, etc.), a message, and optional details for troubleshooting (e.g., safety block reasons).

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