MCP server giving AI coding agents offline, token-efficient persistent memory — recall decisions, patterns, and bugs across sessions with 68.5% fewer tokens than re-reading context. No LLM, no server;
Persistent memory for AI coding agents — remember decisions, patterns, and bugs between sessions.
- What is toon-memory? - Blog Post - Features - Quick Start - Supported Agents - MCP Tools - Tips & Best Practices - CLI Commands - Configuration - How It Works - Why TOON? - Troubleshooting - FAQ - Development - Contributing - License
Ever had that feeling where your AI agent forgets everything from yesterday's session? You explain the same architecture decision for the third time, and it still suggests the approach you already rejected?
toon-memory fixes this. It gives your AI agent a persistent memory that survives restarts, so it actually learns from your project over time.
Scenario What toon-memory does -------------------------------- Design debates "We chose Redis over Memcached because of pub/sub support" Framework choices "This project uses Zod for validation, not Joi" Bug fixes "Redis pool exhaustion — fix was maxconnections=20" Architecture notes "Broker service uses RESP protocol, not HTTP" Onboarding "The deploy script lives in scripts/deploy.sh" Team context "PR 142 reverted the caching change — don't re-add it"
Read How toon-memory Makes Your AI Agent Smarter to see a real-world demo of persistent memory in action.
- 11 MCP tools — Full memory management via Model Context Protocol - MCP Resources — Read memory as context without tool invocations - 15 agents supported — OpenCode, VS Code, Claude Code, Cursor, Windsurf, Cline, Continue, Codex CLI, Gemini CLI, Zed, Antigravity, Aider, KiloCode, OpenClaw, Kiro - Interactive installer — Select which agents to co
From the project README.
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