MCP Gemini CrunchTools
A secure MCP server for Google Gemini AI, providing 39 tools for text, image, video, document, YouTube, research, and more. Runs locally via stdio with API key protection and no third-party services.
README
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-geminibuilt on Hummingbird Python base image
Naming Convention
| Component | Name |
|---|---|
| GitHub repo | crunchtools/mcp-gemini |
| Container | quay.io/crunchtools/mcp-gemini |
| Python package (PyPI) | mcp-gemini-crunchtools |
| CLI command | mcp-gemini-crunchtools |
| Module import | mcp_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 groundinggemini_brainstorm- Generate creative ideas on a topicgemini_analyze_code- Analyze code for security, performance, bugsgemini_analyze_text- Analyze text for sentiment, tone, contentgemini_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 imagesgemini_image_prompt- Craft effective image generation promptsgemini_imagen_generate- Generate images using Google Imagen 4 models
Image Editing (4 tools)
gemini_start_image_edit- Start a multi-turn image editing sessiongemini_continue_image_edit- Continue editing in an active sessiongemini_end_image_edit- End an image editing sessiongemini_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 documentsgemini_extract_tables- Extract tables from documents
URL Tools (3 tools)
gemini_analyze_url- Analyze one or more URLsgemini_compare_urls- Compare two URLsgemini_extract_from_url- Extract specific data from a URL
Video Tools (2 tools)
gemini_generate_video- Generate videos using Veogemini_check_video- Check video generation status
YouTube Tools (2 tools)
gemini_youtube- Analyze YouTube videosgemini_youtube_summary- Summarize YouTube videos
Voice Tools (3 tools)
gemini_speak- Convert text to speechgemini_dialogue- Generate multi-voice dialogue audiogemini_list_voices- List available voices
Research Tools (3 tools)
gemini_deep_research- Perform multi-step web researchgemini_check_research- Check research operation statusgemini_research_followup- Ask follow-up questions
Cache Tools (4 tools)
gemini_create_cache- Create content cache for repeated queriesgemini_query_cache- Query cached contentgemini_list_caches- List all active cachesgemini_delete_cache- Delete a cache
Structured Output Tools (2 tools)
gemini_structured- Get structured JSON outputgemini_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:zflag sets a sharedcontainer_file_tcontext 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
-
Navigate to Google AI Studio
- Go to https://aistudio.google.com/apikey
- Sign in with your Google account
-
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)
-
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
-
API Key Protection
- Stored as SecretStr (never accidentally logged)
- Environment variable only (never in files or args)
- Sanitized from all error messages
-
Input Validation
- Pydantic models for all inputs
- File path validation
- URL validation
- Strict format validation
-
API Hardening
- Hardcoded API base URL (prevents SSRF)
- TLS certificate validation
- Request timeouts
- Response size limits
-
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
- Google Gemini API Documentation
- Google AI Studio
- FastMCP Documentation
- MCP Specification
- crunchtools.com
<!-- mcp-name: io.github.crunchtools/gemini -->
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