nandhakumar-murugan/gemini-antigravity-bridge

Overview

A bridge that connects Google Gemini Spark and Cloud AI to a local machine through the Model Context Protocol (MCP). It enables autonomous file creation, terminal execution, and subagent orchestration. The project is written in Python.

Best for

Best for
Developers prototyping local automation with Google Gemini agents

Use cases

• Letting Gemini create and edit files on a local machine
• Executing terminal commands from an AI agent session
• Coordinating multiple subagents for complex local tasks

How to use

Install

pip install -r requirements.txt

Tools exposed

• run_system_command
• run_batch_commands
• read_file
• write_file
• edit_file
• append_file
• batch_write_files
• create_full_project
• list_directory
• run_agent_task
• get_agent_status
• terminate_task
• get_bridge_history
• save_session_note
• get_session_notes
• sync_project_to_gemini
• git_quick_status
• request_spark_connected_app_action
• get_spark_connected_apps_catalog
• list_antigravity_conversations

Notes

A bridge that connects Google Gemini Spark and Cloud AI to a local machine through the Model Context Protocol (MCP). It enables autonomous file creation, terminal execution, and subagent orchestration. The project is written in Python.

6 stars on GitHub. Last updated 2026-09-07. Licensed Apache-2.0.

Use cases

• Letting Gemini create and edit files on a local machine
• Executing terminal commands from an AI agent session
• Coordinating multiple subagents for complex local tasks

Pros

• Uses the standard MCP protocol for AI integration
• Supports both Gemini Spark and Cloud AI
• Covers file, terminal, and subagent workflows in one tool

Cons

• Very small user base with only 6 stars
• Autonomous terminal execution carries security risks
• Limited evidence of documentation or maintenance

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.