Mnemos: an MCP server for persistent Claude Code memory

Claude Code forgets everything between sessions, forcing you to re-explain conventions, corrections, and context every time. Mnemos (GitHub) is an MCP server that fixes that by storing and replaying persistent memory across sessions.
How it works
- On session start, it pushes a ranked context block (conventions, corrections, skills, hot files, recent session summaries) into Claude's prompt.
- Records corrections as
tried / wrong_because / fix. Three corrections on the same topic auto-promote into a reusable skill withWhen this applies / Avoid / Dosections — deterministic pattern mining, no LLM in the loop. - Bi-temporal store: facts carry valid/invalid timestamps, so "we used to use X, now Y" works without stale context.
- Compaction recovery: one tool call restores the goal and key decisions after Claude Code compacts mid-session.
- Prompt-injection scanner at write boundary (instruction overrides, zero-width unicode, MCP spoofing).
- Retrospective replay: regenerate any past session as markdown with everything learned since layered in, paste it back to Claude, ask "what would I do differently now."
Stack & install
- Single static Go binary, 15 MB. No Python, no Docker, no vector DB, no CGO.
- SQLite + FTS5 retrieval, optional cosine similarity if Ollama is running.
- Install (MIT, free, no paid tier):
curl -fsSL https://raw.githubusercontent.com/polyxmedia/mnemos/main/scripts/install.sh | bash
mnemos init
mnemos initauto-wires Claude Code, Claude Desktop, Cursor, Windsurf, and Codex CLI. Restart your agent andmnemos_*tools show up.
Who it's for
Developers using Claude Code who are tired of re-teaching conventions every session and want reproducible, token-free memory.
📖 Read the full source: r/ClaudeAI
👀 See Also

Open Source Auto-Memory System for LLM Agents Achieves 94% Recall Accuracy
A developer built a memory plugin for LLM-based agents that automatically extracts, classifies, and persists facts across sessions without explicit user commands. The system achieved 94.2% accuracy on a 52-checkpoint recall benchmark using structured markdown files instead of vector databases.

DIY OpenClaw Alternative Using Claude Code in Headless Mode
A developer built a Python server that sends prompts to Claude Code in headless mode, with Telegram bot access, Hammerspoon automation, and local markdown file storage for tasks, schedules, and notes.

OpenClaw memory loss fix using Mem0 plugin
OpenClaw agents experience memory loss due to context compaction rewriting files like MEMORY.md. The Mem0 plugin solves this by moving memory outside the context window with auto-recall and auto-capture features.

Quick-Question Plugin Automates Unity Development with Claude Code
A developer has released quick-question, a macOS plugin for Unity 2021.3+ that automates compilation, testing, and cross-model code review when using Claude Code. The tool includes 20 slash commands and uses a 'Tribunal' pattern where Codex and Claude review each other's findings.