Your AI has amnesia. We fixed it.

Every LLM starts every conversation from zero. Stash gives your agent persistent memory — it remembers, recalls, consolidates, and learns across sessions. No more explaining yourself from scratch.

Open source. Self-hosted. Works with any MCP-compatible agent.

git clone https://github.com/alash3al/stash.git
cd stash
cp .env.example .env   # edit with your API key + model
docker compose up

That's it. Postgres + pgvector, migrations, MCP server with background consolidation — all in one command.

After docker compose up, Stash exposes an MCP server over SSE at:

http://localhost:8080/sse

Point any MCP-compatible client at that URL. Example configs:

Cursor — ~/.cursor/mcp.json

{
  "mcpServers": {
    "stash": {
      "url": "http://localhost:8080/sse"
    }
  }
}

Claude Desktop — claude_desktop_config.json

{
  "mcpServers": {
    "stash": {
      "url": "http://localhost:8080/sse"
    }
  }
}

OpenCode — ~/.config/opencode/config.json

{
  "mcp": {
    "stash": {
      "type": "remote",
      "url": "http://localhost:8080/sse",
      "enabled": true
    }
  }
}

Windsurf — ~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "stash": {
      "url": "http://localhost:8080/sse"
    }
  }
}

Works with any agent that supports MCP over SSE — Claude Desktop, Cursor, Windsurf, Cline, Continue, OpenAI Agents, Ollama, OpenRouter, and more.

Stash is a cognitive layer between your AI agent and the world. Episodes become facts. Facts become relationships. Relationships become patterns. Patterns become wisdom.

An 8-stage consolidation pipeline turns raw observations into structured knowledge — facts, relationships, causal links, goal tracking, failure patterns, hypothesis verification, and confidence decay. Each stage only processes new data since the last run.

alash3al.github.io/stash →

Apache 2.0