Skip to content

mnemon

⭐ 500 · ✅ active · related · ⬆️ +6 recently
Type related Category Harness
Stars ⭐ 500 Status ✅ active
Author mnemon-dev Updated 2026-08-21

One-liner

LLM-supervised persistent memory for AI agents: graph-based recall and cross-session knowledge in a single binary.

About

LLM-supervised persistent memory for AI agents. --- LLM agents forget everything between sessions. Context compaction drops critical decisions, cross-session knowledge vanishes, and long conversations push early information out of the window. Mnemon gives your agent persistent, cross-session memory — a four-graph knowledge store with intent-aware recall, importance decay, and automatic deduplication. The mnemon memory path remains one local binary with zero API keys and one setup command. Mnemon ships one executable with two separate surfaces. Memory stays at the mnemon root; Agency Preview lives at mnemon agency ... and adds durable, project-local responsibility and effect admission to an existing Pi agent. Agency does not replace Memory or the Agent Runtime.

✨ Key Features

  • Zero user-side operation — install once; supported runtimes can use hooks, minimal runtimes can use persistent rules
  • LLM-supervised — the host LLM decides what to remember, update, and forget; no embedded LLM, no API keys
  • Multi-framework support — Claude Code, Codex, Cursor, ZCode, TRAE/TRAE Work, Qoder/QoderWork, CodeBuddy, WorkBuddy, Kimi Code, OpenCode, and Hermes Agent (h
  • Runtime-native integration — runtime-specific SKILL.md, shared guide.md, and supported hooks or extensions
  • Four-graph architecture — temporal, entity, causal, and semantic edges, not just vector similarity
  • Intent-native protocol — three primitives (remember, link, recall) map to the LLM's cognitive vocabulary, not database syntax; structured JSON output
  • Intent-aware recall — graph traversal + optional vector search (RRF fusion), enabled by default for all queries
  • Built-in deduplication — remember auto-detects duplicates and conflicts; skips or auto-replaces

📦 Install

brew install --cask mnemon-dev/tap/mnemon

🚀 Quick Start

go install github.com/mnemon-dev/mnemon@latest

📚 Learn more

Install

Homebrew Cask (macOS): brew install --cask mnemon-dev/tap/mnemon Go install (macOS / Linux / Windows): go install github.com/mnemon-dev/mnemon@latest Windows supports the core Memory commands. Agency remains unavailable on Windows until its local authority boundary has native Windows security. From source (macOS / Linux): git clone https://github.com/mnemon-dev/mnemon.git && cd mnemon

FAQ

Do different sessions share memory? Yes. By default, all sessions use the same default store — a decision remembered in one session is available in every future session. Can I isolate memory per project or agent? Yes. Use named stores to separate memory: mnemon store create work # create a new store mnemon store set work # set as default MNEMON_STORE=work mnemon recall "query" # or use e

Configuration

Retention: Each automatic deletion is soft, appears in the oplog as a prune operation, and is reported by ID in the triggering command's auto_pruned_ids field. Embedding (only relevant if using embeddings): The embedding client speaks the Ollama API by default and the OpenAI-compatible embeddings API when the endpoint ends in /v1 (or when MNEMON_EMBED_PROTOCOL=openai is set). For e