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PavelGuzenfeld

gemini-mcp

by PavelGuzenfeld
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gemini-mcp

npm MCP Registry Node.js License: MIT

Lightweight MCP server that exposes Google Gemini as tools for Claude Code (or any MCP client).

Use Gemini for second opinions, large-context analysis, code review, or anything where a different model perspective helps.

Tools

Tool

Description

gemini_ask

Ask Gemini a question or give it a task

gemini_analyze

Send code/text for analysis with a specific instruction

gemini_chat

Multi-turn conversation with full history

gemini_models

List available Gemini models

Related MCP server: Gemini Bridge

Quick Start

1. Get an API key

Go to Google AI Studio and create a free API key.

2. Install

Option A — Clone (recommended for Claude Code)

git clone https://github.com/PavelGuzenfeld/gemini-mcp.git ~/.claude/mcp-servers/gemini
cd ~/.claude/mcp-servers/gemini
npm install

Option B — npx (no install)

npx claude-gemini-mcp

3. Register with Claude Code

Add to ~/.claude/settings.json:

{
  "mcpServers": {
    "gemini": {
      "command": "node",
      "args": ["/home/you/.claude/mcp-servers/gemini/index.js"],
      "env": {
        "GEMINI_API_KEY": "your-key-here"
      }
    }
  }
}

Or with npx:

{
  "mcpServers": {
    "gemini": {
      "command": "npx",
      "args": ["-y", "claude-gemini-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-key-here"
      }
    }
  }
}

Usage Examples

Ask a question

> Use gemini_ask to explain the difference between std::expected and std::optional

Gemini says: std::optional<T> represents a value that may or may not be present...
std::expected<T, E> additionally carries an error value when the expected value is absent...

Analyze code

> Use gemini_analyze to review this function for performance issues:
  instruction: "Find performance bottlenecks"
  content: <your code here>

Gemini says: Line 12 allocates inside the loop — move the vector outside...

Multi-turn conversation

> Use gemini_chat with messages:
  [{"role": "user", "content": "Design a REST API for a task manager"},
   {"role": "model", "content": "Here's a RESTful design..."},
   {"role": "user", "content": "Now add authentication"}]

Gemini says: Building on the previous design, add JWT-based auth...

Override model per call

> Use gemini_ask with model: "gemini-2.5-flash" to quickly summarize this error log

Environment Variables

Variable

Default

Description

GEMINI_API_KEY

(required)

Google AI Studio API key

GEMINI_MODEL

gemini-2.5-pro

Default model for all tools

Models

Model

Best for

gemini-2.5-pro

Best quality, large context (1M tokens)

gemini-2.5-flash

Fast, good for most tasks

gemini-2.0-flash

Fastest, simple tasks

Every tool accepts an optional model parameter to override the default per-call.

Features

  • Retry with exponential backoff on rate limits (429) and server errors (5xx)

  • Graceful error reporting back to the MCP client (no crashes)

  • Per-call model override

  • Zero configuration beyond the API key

Troubleshooting

Problem

Solution

GEMINI_API_KEY is not set

Add the key to your env block in settings.json

429 Too Many Requests

Built-in retry handles this — wait a few seconds

Model not found

Run gemini_models to list valid model names

Tools not appearing in Claude Code

Check ~/.claude/settings.json syntax, restart Claude Code

ECONNREFUSED

Check network/firewall — the server calls generativelanguage.googleapis.com

Development

git clone https://github.com/PavelGuzenfeld/gemini-mcp.git
cd gemini-mcp
npm install
npm test          # Run smoke tests
node index.js     # Start the MCP server locally

License

MIT

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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