MCP Gemini

Name: MCP Gemini
Author: crunchtools

by crunchtoolsversion 0.3.0i★ –iRuns on your computer

Registry nameio.github.crunchtools/gemini

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Design, images & audio

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "gemini": {
      "command": "uvx",
      "args": [
        "mcp-gemini-crunchtools"
      ]
    }
  }
}

Run this in your terminal

claude mcp add gemini -- uvx mcp-gemini-crunchtools

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "gemini": {
      "command": "uvx",
      "args": [
        "mcp-gemini-crunchtools"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "gemini": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "mcp-gemini-crunchtools"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account crunchtools, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Design, images & audioi

More stars than 0% of the other 2180 servers in this category
Published to the registry more recently than 2% of the other 2180 servers in this category
Basic checks equal to or better than 100% of the other 2180 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is MCP Gemini safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.3.0) reached the registry 8 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Figma Context MCP

by GLips

Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.

Runs on your computer★ 16,165MITUpdated 5 months ago

Install

Claude Real Video

by HUANGCHIHHUNGLeo

Let any LLM watch a video locally — and search everything it has ever watched.

Runs on your computer★ 2,284MITUpdated 2 months ago

Install

Figma MCP Server

by figma

Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.

Runs in the cloud★ 2,152Updated 13 months ago

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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 - STRIDE threat model (see SECURITY.md), Pydantic input validation, and the API key held as a SecretStr to prevent accidental logging
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

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 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

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.

MCP Gemini

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Design, images & audioi

Common questions

Alternatives

Figma Context MCP

Claude Real Video

Figma MCP Server

README from the maker

MCP Gemini CrunchTools

Overview

Naming Convention

Why Hummingbird?

Features

Query Tools (5 tools)

Image Generation (4 tools)

Image Editing (4 tools)

Image Analysis (1 tool)

Search Tools (1 tool)

Document Tools (3 tools)

URL Tools (3 tools)

Video Tools (2 tools)

YouTube Tools (2 tools)

Voice Tools (3 tools)

Research Tools (3 tools)

Cache Tools (4 tools)

Structured Output Tools (2 tools)

Token Tools (1 tool)

Code Execution Tools (1 tool)

Installation

With uvx (Recommended)

With pip

With Container

Configuration

Creating a Google Gemini API Key

Add to Claude Code

Optional: Set Output Directory (non-container)

Usage Examples

Query with Google Search

Generate an Image

Analyze a PDF Document

Summarize a YouTube Video

Deep Research

Code Analysis

Security

Key Security Features

Development

Setup

Run Tests

Lint and Type Check

Build Container

License

Contributing

Links