Stash lets your AI agent keep memory across conversations, so you don’t have to repeat context every time. It’s an open-source, self-hosted layer that uses Postgres, pgvector, and an eight-stage consolidation pipeline to turn raw observations into structured knowledge. It plugs into any MCP-compatible agent with a single Docker command.

• Stash gives AI agents persistent memory across sessions using Postgres + pgvector, run via a self-hosted Docker stack (no cloud dependency).
• A background service runs an eight-stage consolidation pipeline (fact extraction, relationship mapping, causal links, goal tracking, failure patterns, hypothesis checks, confidence decay) that only processes new entries, keeping the knowledge base efficient as it grows.
• It works with any MCP-compatible agent (OpenAI Agents, Claude Desktop, Continue, Cursor, Windsurf, Ollama, OpenRouter) via a single Docker command setup.
• It's open source (Apache 2.0), letting users customize consolidation rules, swap models, or plug in custom retrieval logic.