Skip to main content
Glama

⚡ Gemini Antigravity Bridge

The World's First Bidirectional MCP Bridge Between Google Gemini Spark & DeepMind Antigravity

PyPI DOI Glama Python MCP License Tests Google Gemini DeepMind Model Support

Connect Google's cloud AI (Gemini Spark powered by Gemini 3.8 / 3.7) to your local agentic IDE (Antigravity) with 23 powerful MCP tools — enabling autonomous task dispatch, shared memory, file operations, and cross-agent orchestration.

Quick Start · Architecture · Tools · Connected Apps · Deploy


🌐 What Is This?

Gemini Antigravity Bridge is an MCP (Model Context Protocol) server that creates a persistent, bidirectional communication channel between:

  • ☁️ Google Gemini Spark (cloud-based AI assistant with Google Workspace access, powered by Gemini 3.8 / 3.7)

  • 💻 Google DeepMind Antigravity (local agentic IDE with full system access)

Optimized for Gemini 3.8's next-generation agentic reasoning, this enables a fully autonomous loop where Spark can dispatch coding tasks to your local machine, and Antigravity can request cloud intelligence back from Spark — all through a standardized, secure protocol.

┌──────────────────────────────────────────────────────────────────┐
│                    GEMINI SPARK (Google Cloud)                    │
│  📬 Gmail │ 📁 Drive │ 📅 Calendar │ 🎨 Canva │ 🎥 YouTube     │
└─────────────────────────┬────────────────────────────────────────┘
                          │ MCP over HTTPS
                          ▼
┌──────────────────────────────────────────────────────────────────┐
│              ⚡ GEMINI ANTIGRAVITY BRIDGE (MCP Server)            │
│                                                                  │
│  🔧 System Commands    📂 File Operations    🤖 Agent Dispatch   │
│  🧠 Shared Memory      🔄 Project Sync       📊 Status Reports  │
│                                                                  │
│  Tunnel: ngrok / Cloudflare (permanent HTTPS domain)             │
└─────────────────────────┬────────────────────────────────────────┘
                          │ Local MCP + Message Injection
                          ▼
┌──────────────────────────────────────────────────────────────────┐
│             ANTIGRAVITY IDE (Local Machine)                       │
│  🖥️ Terminal │ 📝 Code Editor │ 🌳 Git │ 🧪 Tests │ 🚀 Deploy  │
└──────────────────────────────────────────────────────────────────┘

Related MCP server: simple_mcp_demo

🏆 Why This Bridge?

Feature

This Project

Other MCP Servers

Bidirectional Cloud ↔ Local

Autonomous Agent Task Dispatch

Cross-Agent Shared Memory

Antigravity Conversation Injection

Spark Connected Apps Orchestration

Google Workspace Integration

✅ (via Spark)

Partial

Local File System Access

Some

System Command Execution

Some


🚀 Quick Start

Prerequisites

  • Python 3.10+

  • ngrok account (free tier) with a reserved domain

  • Google Gemini Spark (Advanced/Ultra subscription)

  • Google DeepMind Antigravity IDE

Installation

# Clone the repository
git clone https://github.com/nandhakumar-murugan/gemini-antigravity-bridge.git
cd gemini-antigravity-bridge

# Install dependencies or install package directly
pip install -r requirements.txt
# OR install as a CLI tool:
pip install -e .

# Configure environment
cp .env.example .env
# Edit .env with your NGROK_AUTHTOKEN and NGROK_DOMAIN

# Launch the bridge (via script or CLI)
gemini-bridge
# or: python run_with_tunnel.py

Connect to Gemini Spark

  1. Open Gemini Spark → Settings → Connected Apps

  2. Click "Add a custom app"

  3. Enter your public MCP URL: https://your-domain.ngrok-free.dev/mcp

  4. Spark will discover all 23 tools automatically!


🛠️ Available Tools (23)

🔧 System Execution

Tool

Description

run_system_command

Execute any shell/PowerShell command with captured stdout/stderr

run_batch_commands

Run multiple commands sequentially with error handling

📂 File Operations

Tool

Description

read_file

Read file contents from any path on the local machine

write_file

Create or overwrite files with specified content

edit_file

Surgically edit specific lines in existing files

append_file

Append content to the end of a file

batch_write_files

Create multiple files in a single operation

create_full_project

Scaffold an entire project directory structure

list_directory

List directory contents with metadata

🤖 Agent Orchestration

Tool

Description

run_agent_task

Launch an autonomous Antigravity coding subagent

get_agent_status

Check status and output of a running agent task

terminate_task

Kill a running agent task

🧠 Shared Memory & Sync

Tool

Description

get_bridge_history

Retrieve full cross-client operation history

save_session_note

Write a structured note to shared memory (tagged)

get_session_notes

Read session notes by tag or date range

sync_project_to_gemini

Sync project metadata to Spark's knowledge base

git_quick_status

Quick Git status check for any repository

🌐 Spark Connected Apps

Tool

Description

request_spark_connected_app_action

Dispatch tasks to Spark's connected apps (@Canva, @YouTube, @Gmail, etc.)

get_spark_connected_apps_catalog

List all available connected apps and capabilities

🔗 Antigravity Deep Integration

Tool

Description

list_antigravity_conversations

List all active Antigravity IDE conversations

inject_message

Inject a structured message directly into an Antigravity conversation

send_spark_to_antigravity_task

Dispatch a full task brief from Spark to Antigravity

get_antigravity_agent_report

Get the latest execution report for Spark to review


🔄 Spark Connected Apps

Through the bridge, Antigravity can orchestrate Spark's connected Google & third-party apps:

App

Capabilities

🎨 @Canva

Poster design, infographics, slide decks

📁 @Google Drive

Cloud file search, folder management

📝 @Google Docs

Document creation and collaboration

📌 @Google Keep

Quick notes, flashcards, checklists

🎥 @YouTube

Video search, transcript extraction

📬 @Gmail

Email reading, URL extraction

📓 @Gemini Notebook

Deep research and synthesis

📦 @Dropbox

Cloud storage sync via MCP


🏗️ Architecture

graph TB
    subgraph Cloud["☁️ Google Cloud"]
        Spark["Gemini Spark<br/>Consumer AI Assistant"]
        Gmail["📬 Gmail"]
        Drive["📁 Google Drive"]
        Calendar["📅 Google Calendar"]
        Canva["🎨 Canva"]
    end

    subgraph Bridge["⚡ Antigravity Bridge"]
        MCP["MCP Server<br/>(FastMCP + Starlette)"]
        Tunnel["HTTPS Tunnel<br/>(ngrok / Cloudflare)"]
        Memory["🧠 Shared Memory<br/>(bridge_history.json)"]
        Dashboard["📊 Web Dashboard"]
    end

    subgraph Local["💻 Local Machine"]
        AGY["Antigravity IDE"]
        Terminal["🖥️ Terminal"]
        Git["🌳 Git Repos"]
        Files["📂 File System"]
    end

    Spark -->|"MCP over HTTPS"| Tunnel
    Tunnel --> MCP
    MCP -->|"inject_message"| AGY
    MCP -->|"run_system_command"| Terminal
    MCP -->|"git_quick_status"| Git
    MCP -->|"read/write_file"| Files
    MCP --> Memory
    AGY -->|"save_session_note"| Memory
    Memory -->|"get_agent_report"| Spark
    Spark --> Gmail
    Spark --> Drive
    Spark --> Calendar
    Spark --> Canva

🚢 Deployment

Auto-Start on Windows Boot

The bridge includes a silent startup script that launches automatically when you log in:

📁 %APPDATA%\Microsoft\Windows\Start Menu\Programs\Startup\
└── GeminiAntigravityBridge.vbs  (silent background launcher)

Cloud Deployment (24/7 Uptime)

# Using Docker
docker build -t gemini-antigravity-bridge .
docker run -d -p 8000:8000 --env-file .env gemini-antigravity-bridge

# Using Render.com / Google Cloud Run
# Push to GitHub → Connect repo → Deploy automatically

📋 Scheduled Monitoring

The bridge supports multi-tier automated monitoring via Gemini Spark schedules:

Tier

Cadence

Purpose

🔴 Instant Trigger

Real-time (on email arrival)

Zero-delay alerts for college & NPTEL emails

🟡 Hourly Sweep

Every 60 minutes

Broad monitoring across all platforms

🟢 Morning Briefing

Daily @ 8:00 AM

Strategic daily plan with exam schedules


🤝 Contributing

Contributions are welcome! Please read the Apache 2.0 License before submitting PRs.

  1. Fork the repository

  2. Create your feature branch (git checkout -b feat/amazing-feature)

  3. Commit your changes (git commit -m 'feat: add amazing feature')

  4. Push to the branch (git push origin feat/amazing-feature)

  5. Open a Pull Request


📄 License

This project is licensed under the Apache License 2.0 — see the LICENSE file for details.


📚 Research Paper & Academic Citation

This framework implements the formal architecture introduced in the published research paper:

AgentShield: A Zero-Trust Runtime Guardrail Architecture for Autonomous Multi-Agent AI Systems with Bidirectional Context Synchronization
Nandhakumar Murugan
Department of Computer Science and Engineering (Cybersecurity), KGiSL Institute of Technology (KiTE), Autonomous
Permanent DOI: 10.5281/zenodo.22259022 | Open Access: Zenodo CERN Repository

If you reference or build upon this architecture in academic or enterprise research, please cite:

@article{murugan2026agentshield,
  title={AgentShield: A Zero-Trust Runtime Guardrail Architecture for Autonomous Multi-Agent AI Systems with Bidirectional Context Synchronization},
  author={Murugan, Nandhakumar},
  journal={Zenodo},
  year={2026},
  doi={10.5281/zenodo.22259022},
  url={https://doi.org/10.5281/zenodo.22259022}
}

👨‍💻 Author

Nandhakumar Murugan
B.E. Computer Science & Cyber Security | KGiSL Institute of Technology
Google Student Ambassador (GID: 36) | Open Source Contributor

GitHub LinkedIn


Built with ❤️ using Google Gemini, DeepMind Antigravity & Model Context Protocol

Maintenance

ActivityMaintained
ResponsivenessNo issues

Related MCP Connectors

Related MCP Servers

  • A
    license
    Not graded
    quality
    C
    maintenance
    A comprehensive Model Context Protocol toolkit that transforms AI assistants into autonomous agents capable of executing real-world tasks across filesystems, web requests, Git workflows, databases, system commands, and AI integrations.
    MIT
  • F
    license
    Not graded
    quality
    B
    maintenance
    An AI-powered development assistant that enables LLMs to securely interact with local development tools including Git, filesystem, Docker, PostgreSQL, and GitHub via the Model Context Protocol.

Latest Blog Posts

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/nandhakumar-murugan/gemini-antigravity-bridge'

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