stash

# Stash **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. --- > **Don't want to self-host?** > **[usestash.io](https://usestash.io)** is the hosted cloud version — sign in with Google, copy one MCP URL, and you're done. Free to start. --- ## Quick Start ```bash 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. **Next:** [Getting Started guide](docs/GETTING_STARTED.md) — connect your MCP client, run `init` / `remember` / `recall`, and verify everything works. **Fully local (no cloud API):** [Ollama setup guide](docs/LOCAL_OLLAMA.md) — host Ollama + Docker Compose, private embeddings and reasoner. ## Atlas Cloud > [Atlas Cloud](https://www.atlascloud.ai/?utm_source=github&utm_medium=link&utm_campaign=stash) is a full-modal AI inference platform that gives developers a single AI API to access video generation, image generation, and LLM APIs. Instead of managing multiple vendor integrations, you connect once and get unified access to 300+ curated models across all modalities. > > Check out Atlas Cloud's coding plan promotion: [https://www.atlascloud.ai/console/coding-plan](https://www.atlascloud.ai/console/coding-plan) Stash already supports Atlas Cloud through its OpenAI-compatible API. Set your `.env` like this: ```bash STASH_OPENAI_API_KEY=your-atlas-cloud-api-key STASH_OPENAI_BASE_URL=https://api.atlascloud.ai/v1 STASH_EMBEDDING_MODEL=text-embedding-3-small STASH_REASONER_MODEL=deepseek-ai/DeepSeek-V3-0324 STASH_VECTOR_DIM=1536 ``` Atlas Cloud works well here because Stash only needs: - an embeddings model for vectorization - a chat-capable reasoning model for consolidation - an OpenAI-compatible base URL and API key See [Getting Started](docs/GETTING_STARTED.md) for a fuller configuration checklist. ## MCP Client Setup 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` ```json { "mcpServers": { "stash": { "url": "http://localhost:8080/sse" } } } ``` **Claude Desktop** — `claude_desktop_config.json` ```json { "mcpServers": { "stash": { "url": "http://localhost:8080/sse" } } } ``` **OpenCode** — `~/.config/opencode/config.json` ```json { "mcp": { "stash": { "type": "remote", "url": "http://localhost:8080/sse", "enabled": true } } } ``` **Windsurf** — `~/.codeium/windsurf/mcp_config.json` ```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, Atlas Cloud-backed setups, and more. ## What It Does Stash is a cognitive layer between your AI agent and the world. Episodes become facts. Facts become relationships. Relationships become patterns. Patterns become wisdom. A 9-stage consolidation pipeline turns raw observations into structured knowledge — facts, relationships, causal links, patterns, contradictions, goal tracking, failure patterns, and hypothesis verification. Each stage only processes new data since the last run. ## Stash Cloud (Beta — Free) A hosted, multi-tenant version of Stash is available at **[usestash.io](https://usestash.io/)** and is currently free while in beta. The cloud version is written from scratch — it shares no code with this repository. It is designed from the ground up for scalability, multi-tenancy, and long-term sustainability as a product. Feature sets differ in both directions: some things available here aren't in the cloud, and vice versa. ## Learn More **[alash3al.github.io/stash →](https://alash3al.github.io/stash/)** ## License Apache 2.0