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g1itchbot8888-del/agent-memory

by Various

Memory system for autonomous agents - built by an agent, for agents

G

MCP

g1itchbot8888-del/agent-memory

Added 1 June 2026

Overview

A memory system for autonomous agents, written in Python and built by an agent for use by agents. It provides a way for agents to store and retrieve state or context, though the project has very limited adoption.

Best for

Best for
Developers curious about agent-generated tooling or building experimental agent memory prototypes

Use cases

  • Experimenting with agent-driven development workflows
  • Prototyping memory persistence for small-scale autonomous agents
  • Studying how an agent can design its own memory infrastructure

How to use

Install

pip install openclaw-memory

Tools exposed

  • agent-memory-capture
  • agent-memory-identity

Tested with

Claude Desktop, Claude Code, Cursor

Notes

A memory system for autonomous agents, written in Python and built by an agent for use by agents. It provides a way for agents to store and retrieve state or context, though the project has very limited adoption.

6 stars on GitHub. Last updated 2026-02-27. Licensed MIT.

Use cases

  • Experimenting with agent-driven development workflows
  • Prototyping memory persistence for small-scale autonomous agents
  • Studying how an agent can design its own memory infrastructure

Pros

  • Lightweight Python implementation suitable for learning
  • Follows the novel concept of agent self-building its tools
  • Publicly available on GitHub for inspection and modification

Cons

  • Only 6 GitHub stars indicates minimal community validation or use
  • Lacks evidence of documentation, tests, or stability
  • Unclear whether the system works reliably beyond the original author’s context

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

Pros

  • Lightweight Python implementation suitable for learning
  • Follows the novel concept of agent self-building its tools
  • Publicly available on GitHub for inspection and modification

Cons

  • Only 6 GitHub stars indicates minimal community validation or use
  • Lacks evidence of documentation, tests, or stability
  • Unclear whether the system works reliably beyond the original author's context
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