Which integrations are available for this server?

Bridges Google's Gemini CLI to MCP-compatible AI assistants, enabling prompt execution, model listing, and raw CLI commands using existing Gemini authentication.

How do I use @staticpayload/gemini-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@@staticpayload/gemini-mcp Explain quantum computing in simple terms" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

@staticpayload/gemini-mcp

by scalarian

Overview Schema Related Servers Score Discussions

JavaScript

Local

┌─────────────────────────────────────────────────────────────────┐
│                                                                 │
│   Claude / Cursor / Any MCP Client                              │
│                    │                                            │
│                    ▼                                            │
│   ┌─────────────────────────────────────┐                       │
│   │     @staticpayload/gemini-mcp       │                       │
│   │   ┌─────────┐ ┌─────────┐ ┌───────┐ │                       │
│   │   │ prompt  │ │ models  │ │  raw  │ │   ◄── MCP Tools       │
│   │   └────┬────┘ └────┬────┘ └───┬───┘ │                       │
│   └────────┼───────────┼─────────┼──────┘                       │
│            │           │         │                              │
│            └───────────┼─────────┘                              │
│                        ▼                                        │
│            ┌───────────────────────┐                            │
│            │    Gemini CLI         │   ◄── Your existing auth   │
│            │    (gemini binary)    │       & configuration      │
│            └───────────────────────┘                            │
│                                                                 │
└─────────────────────────────────────────────────────────────────┘

✨ Features

🔌 Zero Configuration

Uses your existing Gemini CLI installation and authentication. No API keys to manage, no duplicate auth flows.

🚀 Universal Access

⚡ Production Ready

Health checks, graceful shutdown, 5-minute timeouts, proper signal handling. Built for reliability.

🛠️ Three Powerful Tools

Prompt execution, model listing, and raw CLI access for advanced use cases.

Related MCP server: Gemini CLI MCP Server

🚀 Quick Start

Prerequisites

# Install Gemini CLI globally
npm install -g @google/gemini-cli

# Authenticate (run once)
gemini

Run the MCP Server

npx @staticpayload/gemini-mcp

That's it. The server starts and waits for MCP connections via stdio.

🔧 Tools

`gemini_prompt`

Send a prompt to Gemini and get a response.

Parameter	Type	Required	Description
`prompt`	string	✅	The prompt to send
`model`	string	❌	Model override (e.g., `gemini-2.5-flash`)

`gemini_models`

List all available Gemini models.

No parameters required.

`gemini_raw`

Execute any Gemini CLI command with raw arguments.

Parameter	Type	Required	Description
`args`	string[]	✅	CLI arguments array

Example: ["--version"] or ["-p", "Hello", "-m", "gemini-2.5-pro"]

📋 Usage

With Claude Desktop

Add to your Claude configuration (~/.claude/config.json):

{
  "mcpServers": {
    "gemini": {
      "command": "npx",
      "args": ["@staticpayload/gemini-mcp"]
    }
  }
}

With Claude CLI

claude mcp add gemini -- npx @staticpayload/gemini-mcp

With Cursor / Windsurf

Add to your MCP settings:

{
  "gemini": {
    "command": "npx",
    "args": ["@staticpayload/gemini-mcp"]
  }
}

⚙️ Configuration

Environment Variables

Variable	Description
`GEMINI_CLI_PATH`	Override the Gemini binary location
`GEMINI_API_KEY`	Gemini API key (if not using OAuth)
`GOOGLE_APPLICATION_CREDENTIALS`	Service account credentials path

Inherited Configuration

The server inherits your full environment, so existing Gemini configuration works automatically:

~/.config/gemini/          ← CLI configuration
~/.gemini/settings.json    ← Gemini settings
GEMINI_* env vars          ← All Gemini environment variables
gcloud auth                ← Application default credentials

🤖 Autonomous Setup

For production deployments with Vertex AI authentication and zero interactive prompts, use the automated setup:

# 1. Copy environment template
cp .env.example .env

# 2. Edit .env with your GCP project
# PROJECT_ID=your-gcp-project-id

# 3. Authenticate with gcloud
gcloud auth application-default login

# 4. Run automated setup
./setup-gemini.sh

# 5. Use Gemini autonomously
./run-gemini.sh

Features:

✅ Vertex AI authentication (no API keys)
✅ No permission prompts for file/shell/web operations
✅ GA/Preview model routing
✅ MCP server integration
✅ Sandbox directory (avoids macOS permission issues)

See GEMINI_SETUP.md for complete documentation.

🔬 How It Works

┌──────────────┐     stdio      ┌─────────────────┐     spawn     ┌─────────────┐
│  MCP Client  │ ◄────────────► │  gemini-cli-mcp │ ◄───────────► │ gemini CLI  │
│  (Claude)    │   JSON-RPC     │    (Node.js)    │   child proc  │  (binary)   │
└──────────────┘                └─────────────────┘               └─────────────┘

MCP Client sends JSON-RPC requests over stdio
gemini-cli-mcp translates MCP tool calls to Gemini CLI commands
Gemini CLI executes with your existing auth & config
Response flows back through the same path

The server is a thin translation layer—all heavy lifting happens in Gemini CLI.

🏗️ Architecture

@staticpayload/gemini-mcp/
├── src/
│   └── index.js      # MCP server (single file, ~300 lines)
├── package.json      # npm package with bin entry
└── README.md

Design Principles:

Single responsibility: translate MCP ↔ Gemini CLI
Zero global state
Fail fast with clear errors
Minimal dependencies (@modelcontextprotocol/sdk, zod)

🐛 Troubleshooting

"Gemini CLI not found"

# Ensure gemini is installed and in PATH
which gemini

# Or set the path explicitly
export GEMINI_CLI_PATH=/path/to/gemini

"Auth method not set"

# Option 1: Run Gemini CLI once to authenticate
gemini

# Option 2: Set API key
export GEMINI_API_KEY=your-api-key

Server not responding

Check stderr output for health check results:

[gemini-mcp] Gemini CLI: /usr/local/bin/gemini (0.22.4)

📄 License

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

Need Help?

Related Servers

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly
Lightport: Open-Sourcing Glama's AI Gateway
By punkpeye on April 27, 2026.
OpenAI
open source

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/scalarian/gemini.mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server