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README.md

📚 Antigravity Workspace Documentation

Welcome to the comprehensive documentation for the Antigravity Workspace Template — a production-grade starter kit for building autonomous AI agents on Google Antigravity.

🎯 Quick Navigation

Getting Started

Core Features

Planning & Vision

🌟 Key Features

🧠 Infinite Memory Engine

Recursive summarization automatically compresses history—context limits are a thing of the past.

🛠️ Universal Tool Protocol

Generic ReAct pattern. Just register any Python function in src/tools/, and the Agent learns to use it automatically.

⚡️ Gemini Native

Optimized for Gemini 2.0 Flash's speed and function calling capabilities.

🔌 External LLM Support

Call any OpenAI-compatible API via the built-in call_openai_chat tool (supports OpenAI, Azure, Ollama).

🚀 Common Tasks

I want to...

Task Documentation
Get started with the agent Quick Start
Build a custom tool Zero-Config Features
Connect to an MCP server MCP Integration
Use multiple agents Multi-Agent Swarm
Understand the architecture Project Philosophy
See what's coming Development Roadmap

📊 Project Structure

.
├── .antigravity/        # 🛸 Antigravity config/rules
├── .context/            # 📚 Knowledge base auto-injected
├── artifacts/           # 📂 Agent outputs (plans, logs, visuals)
├── src/                 # 🧠 Agent source code
│   ├── agent.py         # Main agent loop
│   ├── memory.py        # JSON memory manager
│   ├── mcp_client.py    # MCP integration
│   ├── swarm.py         # Multi-agent orchestration
│   ├── agents/          # Specialist agents
│   │   ├── base_agent.py
│   │   ├── coder_agent.py
│   │   ├── reviewer_agent.py
│   │   └── researcher_agent.py
│   └── tools/           # Tool implementations
│       ├── demo_tool.py
│       └── mcp_tools.py
├── tests/               # ✅ Test suite
├── scripts/             # 🧪 Utility scripts
├── docker-compose.yml   # Local dev stack
├── README.md            # Main landing page
└── requirements.txt     # Python dependencies

🎓 Documentation by Role

For Developers

  1. Start with Quick Start
  2. Learn Zero-Config tool discovery
  3. Explore the swarm protocol

For DevOps/Deployment

  1. Read Quick Start Docker section
  2. Check Development Roadmap Phase 9 (Enterprise Core)
  3. Configure MCP servers in MCP Integration

For Architects

  1. Understand Project Philosophy
  2. Study Multi-Agent Swarm architecture
  3. Review Development Roadmap vision

For Contributors

  1. Read Project Philosophy
  2. Check Development Roadmap Phase 9
  3. Open an issue to propose ideas

🔗 External Resources

❓ FAQ

Q: Can I use this with OpenAI instead of Gemini?
A: Yes! Set OPENAI_BASE_URL and OPENAI_API_KEY in .env. See Quick Start for details.

Q: How do I add a custom tool?
A: Drop a Python file in src/tools/ with your functions. No registration needed! See Zero-Config Features.

Q: How do I deploy to production?
A: Use Docker! See Quick Start Docker section.

Q: Can I use multiple agents?
A: Yes! Use the swarm system. See Multi-Agent Swarm.

Q: How do I add context/knowledge?
A: Create files in .context/ directory. They're automatically loaded! See Zero-Config Features.

🤝 Contributing

We welcome contributions at all levels:

Report Issues

Found a bug? Open an issue

Suggest Ideas

Have an architectural idea? Ideas are contributions too!
Propose your thought

Submit Code

Ready to code? Check the Roadmap Phase 9 for open areas.

Improve Docs

See a typo or unclear section? Submit a PR to improve the docs!

📞 Support

👥 Contributors

  • @devalexanderdaza — First contributor. Implemented demo tools, enhanced agent functionality, proposed the "Agent OS" roadmap, and completed MCP integration.
  • @Subham-KRLX — Added dynamic tools and context loading (Fixes #4) and the multi-agent cluster protocol (Fixes #6).

📄 License

This project is licensed under the MIT License. See LICENSE for details.


Latest Update: December 2025
Version: Phase 8 (MCP Integration) ✅

Happy building with Antigravity! 🚀