Amp

🚀 AMP: The Agent Memory Protocol 🧠

The Open Standard for Agentic Memory.

This project provides an open - standard protocol for agentic memory, enabling agents to have a continuous and evolving sense of self, and offering multiple ways to visualize and query agent memories.

🚀 Quick Start

1. Install via uv (Recommended)

# Install the tool
uv tool install amp-memory

# Start the brain
amp serve

2. Or, Install via pip

pip install amp-memory
amp serve

3. Open the Dashboard

Visit http://localhost:8000. The interface is Galaxy Mode by default. Switch to Force Mode to see physics - based connections.

4. Connect to IDEs & Tools

AMP works native with Antigravity, Cursor, VS Code Copilot, and Claude Desktop. Add this to your MCP configuration file (usually mcp_config.json or claude_desktop_config.json):

{
  "mcpServers": {
    "amp-memory": {
      "command": "uv",
      "args": ["tool", "run", "amp-memory", "serve"],
      "env": {
        "PYTHONPATH": "."
      }
    }
  }
}

Now you can say:

"@amp remember that I am refactoring the login controller." "@amp what was the last bug we fixed?"

It knows.

✨ Features

🌌 Galaxy View (Visualization)

Don't just guess what your agent knows. See it. AMP comes with a stunning, 60fps local dashboard. Watch memories form constellations in real - time. Nodes cluster by semantic meaning—if two ideas are related, they physically move together.

🕸️ Force Mode (Physics)

Toggle to Force Mode to see the topological connections between your memories. It uses a physics simulation (D3.js) to show you how different memory clusters are "pulled" together by shared context.

🔍 Semantic Query

Stop guessing keywords. Query your agent's memory using natural language. I built a dedicated interface that not only finds relevant memories but shows you the Relevance Score (0 - 100%) so you know exactly why a memory was retrieved.

🔌 MCP Native (Plug & Play)

Built from day one for the Model Context Protocol.

• Claude Desktop: Add AMP to your config, and Claude remembers you forever.
• Cursor: Give your coding assistant persistent context of your project history.

🧠 The "3 - Layer" Brain

I don't just dump text into a vector store. I structure it:

1. ⚡ STM (Short Term): High - fidelity buffer. "What are we doing right now?"
2. 📚 LTM (Long Term): Consolidated insights. "What did we learn last week?"
3. 🕸️ Graph: Connections between entities. "How is function A related to bug B?"

🏆 Best - in - Class Recall

I benchmarked AMP against the leading competitor (Mem0) on the complex LoCoMo dataset. The results weren't close.

📚 Documentation

The (Short) Story

I was tired of building AI agents that forgot everything the moment I closed the terminal.

RAG (Retrieval Augmented Generation) is great for documents, but terrible for experience. It chunks text blindly, losing the narrative. When I asked my agents "Why did we decide this yesterday?", they gave me hallucinated nonsense.

So I built AMP. It's not just a database; it's a Hippocampus for your agents. It mimics the human brain's distinction between Working Memory (Short - term context) and episodic Long - Term Memory, giving your agents a continuous, evolving sense of self.

Why developers are switching to AMP?

The above features of AMP, such as Galaxy View, Force Mode, Semantic Query, MCP Native, the "3 - Layer" Brain, and best - in - class recall, provide developers with a more intuitive, efficient, and accurate way to manage and utilize agent memories, which is why developers are switching to AMP.

🗺️ Roadmap

• [x] Galaxy View: Visual Semantic Space.
• [x] Graph API: D3.js powered visualization.
• [x] Semantic Search: Vector - based relevance sorting.
• [ ] Cloud Sync: Sync memories across devices.
• [ ] Multi - Agent Swarm: Shared memory for agent teams.

⭐ Star History

Made with ❤️ by Akshay.