Uranid

Mnem — AI skill for Claude Code

AI community

Git for AI Agent Knowledge.

How to install Mnem

This entry records only its repository, not the path inside it, so there is no exact command to give. Open Uranid/mnem and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Mnem does

Git for AI Agent Knowledge. A persistent, versioned memory layer for AI systems. Hybrid GraphRAG retrieval. Runs entirely offline.

Alternatives in AI

  • Hindsight — State-of-the-art long-term memory for AI agents by Vectorize 6.7k ★
  • Osaurus — Own your AI. The native macOS harness for AI agents -- any model, persistent memory, autonomous execution, cry 5.1k ★
  • RAG Skill — A Skill dedicated to local knowledge base retrieval 712 ★

README



mnem: Git for AI Agent knowledge

[![License: Apache-2.0](https://img.shields.io/badge/license-Apache--2.0-blue?style=for-the-badge)](LICENSE) [![CI](https://img.shields.io/github/actions/workflow/status/Uranid/mnem/ci.yml?style=for-the-badge&label=CI)](https://github.com/Uranid/mnem/actions/workflows/ci.yml) [![crates.io](https://img.shields.io/crates/v/mnem-cli?style=for-the-badge)](https://crates.io/crates/mnem-cli) [![PyPI](https://img.shields.io/pypi/v/mnem-cli?style=for-the-badge)](https://pypi.org/project/mnem-cli/) [![npm](https://img.shields.io/npm/v/mnem-cli?style=for-the-badge)](https://www.npmjs.com/package/mnem-cli) [![MSRV 1.95](https://img.shields.io/badge/MSRV-1.95-orange?style=for-the-badge)](rust-toolchain.toml) [![Runs on Linux macOS Windows WASM](https://img.shields.io/badge/runs%20on-linux%20%7C%20macos%20%7C%20windows%20%7C%20wasm-2ea44f?style=for-the-badge)](#install)

[English](README.md)  ·  [中文](README.zh-CN.md)  ·  [Español](README.es.md)


**mnem is Git for AI Agent Knowledge.** A persistent, versioned knowledge layer for AI agents, with best-or-tied recall on every public benchmark we tested.

Drop in source code, PDFs, Markdown docs, conversation exports, or whole directories and mnem parses, chunks, and indexes them in one command. File types are auto-detected: heading-aware chunking for Markdown, function- and class-level parsing for source code across many languages, sliding-window extraction for PDFs. No LLM call at ingest, so the same input always produces the same graph; re-ingesting an unchanged file is a no-op.

Skills, decisions, and conventions live as nodes and typed edges in a queryable knowledge graph inside your project's `.mnem/` directory. Commit it alongside your code and every teammate's agents start from the same baseline; branch, diff, merge, or roll back any write the same way you wou