MuscleMemory

MuscleMemory is an open-source procedural memory tool for AI agents that learns from successful and failed coding sessions.

MuscleMemory watches coding agents work and learns procedural tasks when tests pass. It provides agents with short notes on files to change and tests to run for similar tasks in future sessions. The system verifies sessions twice, learns from failures to avoid dead ends, and keeps users in charge by requiring approval before agents see skills. It runs locally using SQLite and a small on-device model, or PostgreSQL with pgvector for teams. Supported integrations include Claude Code, Codex, Cursor, CleanSlate, MCP clients, browser agents, and Python or TypeScript SDKs.

MuscleMemory at a glance

Best for: Software engineer
Runs on: Web, API, VS Code, CLI, self-hosted, open source
Pricing: Free
Released: October 2026
Category: AI agent tool
Website: github.com/thewariend/musclememory

Key features

Learns procedural memory from successful and failed agent sessions
Verifies skills through subsequent session checks and test validation
Shares learned skills between different AI agents
Exports proven skills as SKILL.md files
Stores data locally using SQLite by default
Supports PostgreSQL with pgvector for team setups
Provides MCP tools including recall, observe, learn, evaluate, and inspect

Use it for

Reducing input tokens and tool calls for coding agents
Sharing learned skills between Codex, Claude Code, and Cursor
Capturing reusable procedures from verified agent sessions
Preventing agents from repeating past dead ends

Alternatives to MuscleMemory

AgentMemory — It runs locally with zero external databases and achieves high retrieval recall.
Agentmemoryrepo — Enables agents to navigate memories like a wiki and share knowledge across sessions.
memU — It gives every connected agent a shared and inspectable memory layer.
claude-mem — It shares persistent, searchable agent memory across sessions and devices.
Supermemory — Integrates long-term memory into AI coding agents with a single prompt.
memsearch — It shares continuous context across Claude Code, Codex, and other AI coding agents.
OptMem — Provides permanent agent memory with fast lookups and no background processes.
SimpleMem — Provides semantic lossless compression to reduce token consumption and maintain long-term context.
MemMachine — Provides long-term persistent memory for LLM-based agents.
Mem0 — It provides drop-in persistent memory for AI agents without changing pipelines.
TenseMem — Keeps one current value per slot and refuses to learn from its own output.
MemPalace — Achieves high recall with local-first storage and zero API calls.

All MuscleMemory alternatives