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MewCP Google Gemini MCP

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Hosted, Stateless & Multitenant Gemini MCP server enables AI assistants to access multimodal AI capabilities, content generation, and reasoning workflows through Google Gemini.

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Access Google's most capable AI models through a single MCP tool.

A Model Context Protocol (MCP) server that exposes Google Gemini's API for generating text using state-of-the-art large language models.

Overview

The mewcp-gemini MCP Server provides direct access to Google's Gemini LLMs:

  • Generate high-quality text responses from natural language prompts
  • Choose between fast and capable Gemini model variants
  • Integrate Gemini's reasoning into any MCP-compatible AI workflow

Perfect for:

  • AI agents that need to delegate subtasks to a powerful LLM
  • Generating summaries, translations, code, or creative content
  • Augmenting workflows with Gemini's reasoning and language capabilities

Tools

generate_text — Generate text using Gemini LLM

Generate text using Gemini LLM

Inputs:

- `query` (string, required) — Required. Natural language prompt to send to Gemini. Any text is accepted; no length limit is enforced by this tool.
- `model` (string, optional, default: gemini-2.5-flash) — Optional. Gemini model name, e.g., 'gemini-2.5-flash' or 'gemini-2.5-pro'. Defaults to 'gemini-2.5-flash'.

Output data schema:

{
  prompt: string;
  response: string;
}

API Parameters Reference

Response Envelope

Every tool returns the same top-level envelope. Only data varies per tool.

// Success
{
  "success": true,
  "statusCode": 200,
  "retriable": false,
  "retry_after_seconds": null,
  "error": null,
  "data": { ... }
}

// Error
{
  "success": false,
  "statusCode": 400,
  "retriable": false,
  "retry_after_seconds": null,
  "error": { "code": "{ERROR_CODE}", "message": "{description}", "details": {} },
  "data": null
}
  • retriable — true when it is safe to retry (rate limit, network error, 503). false for validation and auth errors.
  • retry_after_seconds — seconds to wait before retrying; present only when retriable is true and the upstream specifies a delay.
  • error.code — machine-readable string: VALIDATION_ERROR, AUTH_ERROR, UPSTREAM_ERROR, SERVER_ERROR.

Getting Your Gemini API Key

Steps
  1. Go to Google AI Studio API Keys
  2. Sign in with your Google account and navigate to the API keys section
  3. Click Create API Key
  4. Copy the generated key — you will only see it once