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MCP Gemini

MCP server for Google Gemini AI - text, image, video, research, and more

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AI & MLDevelopment Tools
Updated
Mar 2, 2026
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Quick Install

uvx mcp-gemini-crunchtools

MCP Gemini CrunchTools

A secure MCP (Model Context Protocol) server for Google Gemini AI - text, image, video, research, and more.

Overview

This MCP server is designed to be:

  • Secure by default - Comprehensive threat modeling, input validation, and API key protection
  • No third-party services - Runs locally via stdio, your API key never leaves your machine
  • Cross-platform - Works on Linux, macOS, and Windows
  • Automatically updated - GitHub Actions monitor for CVEs and update dependencies
  • Containerized - Available at quay.io/crunchtools/mcp-gemini built on Hummingbird Python base image

Naming Convention

ComponentName
GitHub repocrunchtools/mcp-gemini
Containerquay.io/crunchtools/mcp-gemini
Python package (PyPI)mcp-gemini-crunchtools
CLI commandmcp-gemini-crunchtools
Module importmcp_gemini_crunchtools

Why Hummingbird?

The container image is built on the Hummingbird Python base image from Project Hummingbird, which provides:

  • Minimal CVE exposure - Hummingbird images are built with a minimal package set, dramatically reducing the attack surface compared to general-purpose images
  • Regular updates - Security patches are applied promptly, keeping CVE counts low
  • Optimized for Python - Pre-configured Python environment with uv package manager for fast, reproducible builds
  • Production-ready - Designed for production workloads with proper signal handling and non-root user defaults

This means your MCP server runs in a hardened environment with fewer vulnerabilities than typical Python container images.

Features

Query Tools (5 tools)

  • gemini_query - Query Gemini with optional Google Search grounding
  • gemini_brainstorm - Generate creative ideas on a topic
  • gemini_analyze_code - Analyze code for security, performance, bugs
  • gemini_analyze_text - Analyze text for sentiment, tone, content
  • gemini_summarize - Summarize content in various formats

Image Generation (4 tools)

  • gemini_generate_image - Generate images from text prompts (native Gemini)
  • gemini_generate_image_with_input - Edit/modify existing images
  • gemini_image_prompt - Craft effective image generation prompts
  • gemini_imagen_generate - Generate images using Google Imagen 4 models

Image Editing (4 tools)

  • gemini_start_image_edit - Start a multi-turn image editing session
  • gemini_continue_image_edit - Continue editing in an active session
  • gemini_end_image_edit - End an image editing session
  • gemini_list_image_sessions - List all active editing sessions

Image Analysis (1 tool)

  • gemini_analyze_image - Analyze and describe local image files

Search Tools (1 tool)

  • gemini_search - Web search using Gemini with Google Search grounding

Document Tools (3 tools)

  • gemini_analyze_document - Analyze PDFs, DOCX, TXT, etc.
  • gemini_summarize_pdf - Summarize PDF documents
  • gemini_extract_tables - Extract tables from documents

URL Tools (3 tools)

  • gemini_analyze_url - Analyze one or more URLs
  • gemini_compare_urls - Compare two URLs
  • gemini_extract_from_url - Extract specific data from a URL

Video Tools (2 tools)

  • gemini_generate_video - Generate videos using Veo
  • gemini_check_video - Check video generation status

YouTube Tools (2 tools)

  • gemini_youtube - Analyze YouTube videos
  • gemini_youtube_summary - Summarize YouTube videos

Voice Tools (3 tools)

  • gemini_speak - Convert text to speech
  • gemini_dialogue - Generate multi-voice dialogue audio
  • gemini_list_voices - List available voices

Research Tools (3 tools)

  • gemini_deep_research - Perform multi-step web research
  • gemini_check_research - Check research operation status
  • gemini_research_followup - Ask follow-up questions

Cache Tools (4 tools)

  • gemini_create_cache - Create content cache for repeated queries
  • gemini_query_cache - Query cached content
  • gemini_list_caches - List all active caches
  • gemini_delete_cache - Delete a cache

Structured Output Tools (2 tools)

  • gemini_structured - Get structured JSON output
  • gemini_extract - Extract structured data from text

Token Tools (1 tool)

  • gemini_count_tokens - Count tokens in content

Code Execution Tools (1 tool)

  • gemini_run_code - Execute Python code via Gemini

Total: 39 tools

Installation

With uvx (Recommended)

uvx mcp-gemini-crunchtools

With pip

pip install mcp-gemini-crunchtools

With Container

# Create a shared output directory (required before first run)
mkdir -p ~/.local/share/mcp-uploads-downloads

podman run -v ~/.local/share/mcp-uploads-downloads:/output:z \
    -e GEMINI_API_KEY=your_key \
    -e GEMINI_OUTPUT_DIR=/output \
    quay.io/crunchtools/mcp-gemini

SELinux note: Use :z (lowercase, shared) instead of :Z (uppercase, private). MCP servers run as long-lived stdio processes. With :Z, files copied into the directory after container start won't have the container's private MCS label and will be invisible inside the container. The :z flag sets a shared container_file_t context that all containers and the host can read/write.

Tip: Use the same shared directory (~/.local/share/mcp-uploads-downloads/) across multiple MCP container servers (e.g., mcp-gemini and mcp-wordpress) so generated images are immediately available for WordPress upload without copying.

Configuration

Creating a Google Gemini API Key

  1. Navigate to Google AI Studio

  2. Create API Key

    • Click "Get API key" or "Create API key"
    • Select a Google Cloud project or create a new one
    • Click "Create API key in new project" (or select existing project)

  3. Copy Your API Key

    • IMPORTANT: Copy the API key immediately - store it securely!
    • The key starts with AI... (e.g., AIzaSy...)

Add to Claude Code

claude mcp add mcp-gemini-crunchtools \
    --env GEMINI_API_KEY=your_api_key_here \
    -- uvx mcp-gemini-crunchtools

Or for the container version:

# Create a shared output directory (required before first run)
mkdir -p ~/.local/share/mcp-uploads-downloads

claude mcp add mcp-gemini-crunchtools \
    --env GEMINI_API_KEY=your_api_key_here \
    --env GEMINI_OUTPUT_DIR=/output \
    -- podman run -i --rm \
        -v ~/.local/share/mcp-uploads-downloads:/output:z \
        -e GEMINI_API_KEY \
        -e GEMINI_OUTPUT_DIR=/output \
        quay.io/crunchtools/mcp-gemini

Optional: Set Output Directory (non-container)

For generated images, audio, and videos when running without a container:

claude mcp add mcp-gemini-crunchtools \
    --env GEMINI_API_KEY=your_api_key_here \
    --env GEMINI_OUTPUT_DIR=$HOME/.local/share/mcp-uploads-downloads \
    -- uvx mcp-gemini-crunchtools

Usage Examples

Query with Google Search

User: What are the latest developments in quantum computing?
Assistant: [calls gemini_query with use_google_search=true]

Generate an Image

User: Generate a photorealistic image of a sunset over mountains
Assistant: [calls gemini_generate_image with prompt and style]

Analyze a PDF Document

User: Analyze this research paper at /path/to/paper.pdf
Assistant: [calls gemini_analyze_document with file_path]

Summarize a YouTube Video

User: Summarize this YouTube video: https://youtube.com/watch?v=...
Assistant: [calls gemini_youtube_summary with url]

Deep Research

User: Research the environmental impact of electric vehicles
Assistant: [calls gemini_deep_research then gemini_check_research]

Code Analysis

User: Analyze this Python code for security issues
Assistant: [calls gemini_analyze_code with focus="security"]

Security

This server was designed with security as a primary concern. See SECURITY.md for:

  • Threat model and attack vectors
  • Defense in depth architecture
  • API key handling best practices
  • Input validation rules
  • Audit logging

Key Security Features

  1. API Key Protection

    • Stored as SecretStr (never accidentally logged)
    • Environment variable only (never in files or args)
    • Sanitized from all error messages

  2. Input Validation

    • Pydantic models for all inputs
    • File path validation
    • URL validation
    • Strict format validation

  3. API Hardening

    • Hardcoded API base URL (prevents SSRF)
    • TLS certificate validation
    • Request timeouts
    • Response size limits

  4. Automated CVE Scanning

    • GitHub Actions scan dependencies weekly
    • Automatic PRs for security updates
    • Dependabot alerts enabled

Development

Setup

git clone https://github.com/crunchtools/mcp-gemini.git
cd mcp-gemini
uv sync

Run Tests

uv run pytest

Lint and Type Check

uv run ruff check src tests
uv run mypy src

Build Container

podman build -t mcp-gemini .

License

AGPL-3.0-or-later

Contributing

Contributions welcome! Please read SECURITY.md before submitting security-related changes.

Links

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