AGENTMEMORY — LASTING MEMORY FOR AI CODING AGENTS

AgentMemory is a persistent memory solution designed for AI coding agents. It captures every session, allowing for quick recall in milliseconds and can run on any machine. The tool is built to enhance the functionality of coding agents by providing a memory layer that improves context retention and retrieval without relying on external databases.

1. Auto-Capture Hooks

   AgentMemory features 12 auto-capture hooks that automatically log every tool call, prompt, and session activity into the memory pipeline without requiring additional code.

2. Triple-Stream Retrieval

   The memory system utilizes a hybrid retrieval method combining BM25, vector search, and knowledge graphs, ensuring efficient and accurate recall of information.

3. Hourly Consolidation

   Observations are compressed into semantic memories through hourly sweeps, merging duplicates and decaying stale data to maintain relevance.

4. Replay Functionality

   Users can import JSONL session transcripts to recreate past sessions, including all observations and tool uses.

5. Knowledge Graph Extraction

   The tool extracts entities and relationships during compression, allowing users to query and visualize data through a knowledge graph interface.

6. Peer-to-Peer Federation

   AgentMemory supports synchronization between nodes, enabling memory sharing over authenticated HTTPS connections.

7. Local Data Storage

   The entire runtime operates as a single Node process, storing state data locally in JSON format without the need for external databases like Redis or Postgres.

1. Install AgentMemory using the command: $npm install -g @agentmemory/agentmemory.
2. Start the memory server with $agentmemory to run it on port 3111.
3. Access the real-time viewer at http://localhost:3113 to monitor memory operations.
4. Use the demo command $agentmemory demo to seed sessions and test the hybrid search functionality.
5. For zero-installation, use npx @agentmemory/agentmemory to run the tool without prior setup.

What is AgentMemory?

AgentMemory is a memory runtime designed for AI coding agents, enabling them to capture, recall, and consolidate information efficiently.

How does AgentMemory improve coding agents?

By providing a persistent memory layer, AgentMemory helps coding agents retain context across sessions, reducing the loss of useful project information.

Can I use AgentMemory with any coding agent?

Yes, AgentMemory is compatible with various coding agents and can be integrated easily through its MCP (Memory Control Protocol) interface.

What are the key benefits of using AgentMemory?

The key benefits include fast recall times, local data storage, automatic session capture, and the ability to visualize knowledge graphs.

Price data is not available yet; please visit the official website for more information.

1. AgentMemory effectively enhances the capabilities of coding agents by providing a robust memory system that captures and recalls information seamlessly.
2. The auto-capture feature significantly reduces the need for manual logging, making it user-friendly.
3. However, the reliance on local storage may limit scalability for larger projects or teams that require centralized memory management.
4. The integration process, while straightforward, may still pose challenges for users unfamiliar with coding environments.
5. Overall, AgentMemory presents a strong solution for improving the efficiency of AI coding agents, but further enhancements in scalability and user support could broaden its appeal.