gemini-mcp-connect 1.0.0

Claude Code plugin: Google Gemini as a second-opinion AI via MCP

Gemini Bridge

A Claude Code plugin that connects Claude to Google Gemini models, enabling dual-AI code review, reasoning validation, and critical analysis before applying any changes.

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Plugin Structure

gemini-bridge/
├── .claude-plugin/
│   └── plugin.json          # Plugin metadata & install manifest
├── commands/                # Slash commands
│   ├── gemini.md            # /gemini — query Gemini directly
│   └── gemini-status.md     # /gemini-status — check daily quota
├── agents/
│   └── gemini-reviewer.md   # Specialized dual-AI review agent
├── skills/                  # Focused task skills
│   ├── review-code.md       # /review-code — critical code review
│   └── validate-plan.md     # /validate-plan — plan validation
├── hooks/
│   ├── pre-edit-review.sh   # Pre-edit hook script
│   └── settings-snippet.json# Hook registration snippet
├── .mcp.json                # MCP config (placeholder)
├── gemini_bridge.py         # Core CLI script
└── README.md

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How it works

Before modifying any file, Claude automatically submits its plan or code to Gemini for a critical review (hallucinations, logic flaws, security issues, optimizations). Only after integrating Gemini's feedback does Claude apply the changes.

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Requirements

• Python 3.10+
• A Google Gemini API key → aistudio.google.com
• Claude Code CLI

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Installation

Quick install (recommended)

macOS / Linux:

git clone https://github.com/StealthyLabsHQ/gemini-mcp-connect
cd gemini-bridge
bash install.sh

Windows (PowerShell):

git clone https://github.com/StealthyLabsHQ/gemini-mcp-connect
cd gemini-bridge
.\install.ps1

The installer will:

1. Check Python 3.10+
2. Install google-genai and python-dotenv
3. Copy gemini_bridge.py to ~/.claude/plugins/
4. Ask for your Gemini API key and save it to ~/.claude/plugins/.env
5. Install slash commands to ~/.claude/commands/
6. Add the workflow instructions to ~/.claude/CLAUDE.md
7. Run a connection test

Get your free API key at aistudio.google.com/apikey.

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Manual install

Click to expand manual steps

# 1. Install dependencies
pip install google-genai python-dotenv

# 2. Copy core script
cp gemini_bridge.py ~/.claude/plugins/gemini_bridge.py

# 3. Set your API key
cp .env.example ~/.claude/plugins/.env
# then edit ~/.claude/plugins/.env and set GEMINI_API_KEY

# 4. Install slash commands
cp commands/gemini.md        ~/.claude/commands/gemini.md
cp commands/gemini-status.md ~/.claude/commands/gemini-status.md
cp skills/review-code.md     ~/.claude/commands/review-code.md
cp skills/validate-plan.md   ~/.claude/commands/validate-plan.md

# 5. Add workflow to CLAUDE.md (see CLAUDE.md section in Usage below)

3. Set your API key and configure settings

Copy the example file and fill in your key:

cp .env.example .env

Then edit .env:

GEMINI_API_KEY=your_api_key_here

GEMINI_TEMPERATURE=1.0
GEMINI_MEDIA_RESOLUTION=MEDIUM
GEMINI_THINKING_LEVEL=HIGH
GEMINI_MAX_OUTPUT_TOKENS=65536
GEMINI_TOP_P=0.95

GEMINI_TOOL_CODE_EXECUTION=false
GEMINI_TOOL_GROUNDING_GOOGLE_SEARCH=false
GEMINI_TOOL_GROUNDING_GOOGLE_MAPS=false
GEMINI_TOOL_URL_CONTEXT=false

Get your key at aistudio.google.com/apikey — free tier available.

4. Install globally (recommended)

Place the script in the Claude global plugins folder so it works across all your projects without copying anything:

C:/Users/<you>/.claude/plugins/gemini_bridge.py
C:/Users/<you>/.claude/plugins/.env

Then add the workflow instructions to your global CLAUDE.md:

C:/Users/<you>/.claude/CLAUDE.md

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Usage

# Default (pro tier)
python gemini_bridge.py "Your question or code here"

# Choose a tier
python gemini_bridge.py --tier lite  "question"   # fast & cheap
python gemini_bridge.py --tier flash "question"   # balanced
python gemini_bridge.py --tier pro   "question"   # max reasoning (default)

# Check your daily quota
python gemini_bridge.py --status

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Models

Tier	Model	Description
lite	gemini-3.1-flash-lite-preview	Lightweight, fast, cost-efficient
flash	gemini-3-flash-preview	Balanced — speed + intelligence
pro	gemini-3.1-pro-preview	SOTA reasoning, max depth (default)

Settings applied (pro & flash)

All settings are configurable via .env. Defaults from .env.example:

Parameter	.env.example default	Effect
GEMINI_TEMPERATURE	1.0	0.0 = deterministic → 2.0 = max creativity
GEMINI_THINKING_LEVEL	HIGH	OFF / LOW / MEDIUM / HIGH (pro & flash only)
GEMINI_MEDIA_RESOLUTION	MEDIUM	LOW / MEDIUM / HIGH
GEMINI_TOP_P	0.95	Token sampling breadth (0.0 → 1.0)
GEMINI_MAX_OUTPUT_TOKENS	65536	Max response length

Thinking budget mapping:

Level	thinking_budget
OFF	0 (disabled)
LOW	1024
MEDIUM	4096
HIGH	8192

Tools (disabled by default)

GEMINI_TOOL_CODE_EXECUTION=false
GEMINI_TOOL_GROUNDING_GOOGLE_SEARCH=false
GEMINI_TOOL_GROUNDING_GOOGLE_MAPS=false
GEMINI_TOOL_URL_CONTEXT=false

Set any to true in your .env to enable it.

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Pricing & Cost Estimation

Pricing is per 1 million tokens (input + output combined).

Price table

Model	Input	Output	Notes
gemini-3.1-flash-lite-preview	$0.25 / 1M	$1.50 / 1M	Text, image & video
gemini-3-flash-preview	$0.50 / 1M	$3.00 / 1M	All context lengths
gemini-3.1-pro-preview	$2.00 / 1M	$12.00 / 1M	≤ 200K tokens
gemini-3.1-pro-preview	$4.00 / 1M	$18.00 / 1M	> 200K tokens

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Real cost per request — worked example

Assume a typical Claude Code review request:

• Input: ~2,000 tokens (your plan/code + review prompt)
• Output: ~1,000 tokens (Gemini's critique)

gemini-3.1-pro-preview (pro tier)

Input cost  = 2,000 / 1,000,000 × $2.00  = $0.004000
Output cost = 1,000 / 1,000,000 × $12.00 = $0.012000
─────────────────────────────────────────────────────
Cost per request                          ≈ $0.016

How many requests for $1.00?

$1.00 / $0.016 = ~62 requests

Daily budget at 100 requests/day:

100 × $0.016 = $1.60 / day  →  ~$48 / month

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gemini-3-flash-preview (flash tier)

Input cost  = 2,000 / 1,000,000 × $0.50 = $0.001000
Output cost = 1,000 / 1,000,000 × $3.00 = $0.003000
────────────────────────────────────────────────────
Cost per request                         ≈ $0.004

How many requests for $1.00?

$1.00 / $0.004 = ~250 requests

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gemini-3.1-flash-lite-preview (lite tier)

Input cost  = 2,000 / 1,000,000 × $0.25 = $0.000500
Output cost = 1,000 / 1,000,000 × $1.50 = $0.001500
────────────────────────────────────────────────────
Cost per request                         ≈ $0.002

How many requests for $1.00?

$1.00 / $0.002 = ~500 requests

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Cost comparison summary

Tier	Cost/request	Requests for $1	Requests for $10
lite	~$0.002	~500	~5,000
flash	~$0.004	~250	~2,500
pro	~$0.016	~62	~625

Note: Requests with longer inputs (large code blocks, full files) will cost proportionally more. The pro tier with thinking_budget=8192 also consumes additional tokens for internal reasoning steps.

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Rate limit

The pro tier is rate-limited to 100 requests/day by default to control costs (~$1.60/day max).

python gemini_bridge.py --status
# Gemini Bridge quota — 2026-03-31
#   pro    :   5/100 used  (95 remaining)
#   lite   : unlimited
#   flash  : unlimited

To change the limit, edit RATE_LIMITS in gemini_bridge.py:

RATE_LIMITS = {
    "pro": 100,  # requests per day
}

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File structure

gemini-bridge/
├── gemini_bridge.py   # Main script
├── .env               # Your config & API key (never commit this)
├── .env.example       # Template — safe to commit
├── .gitignore         # Excludes .env
├── rate_limit.json    # Auto-generated daily counter
└── README.md

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License

MIT