remind-mcp

# Remind [](https://pypi.org/project/remind-mcp/) [](https://www.python.org/downloads/) [](LICENSE) Agent-driven memory layer for LLMs. Remind is a deterministic memory substrate with temporal facts, semantic retrieval, and structured curation — the calling agent is the only intelligence. **[Documentation](https://sandst1.github.io/remind/)** · **[Examples](https://sandst1.github.io/remind/examples/)** · **[Changelog](https://sandst1.github.io/remind/reference/changelog)**  ## Quick start ```bash pip install remind-mcp ``` **No configuration required** — Remind uses local embeddings by default (fastembed, no API key). ```bash remind remember "This project uses React with TypeScript" remind remember "Chose PostgreSQL for the database" -t decision remind remember "Cache TTL is 600 seconds" -t fact -e concept:caching remind recall "What tech stack are we using?" ``` ## How it works Remind stores **episodes** (raw experiences) and **concepts** (generalized knowledge). You capture and curate memories explicitly using CLI commands or MCP tools. For **facts** (`-t fact`), Remind automatically: 1. Creates a `Fact` row with validity tracking 2. Assigns it to a cluster based on entity overlap (Jaccard similarity) 3. Detects potential collisions with existing facts — same-cluster collisions and cross-cluster related facts are returned with ready-to-paste `apply` commands For any `remember` call, the output also surfaces the **top-5 nearest episodes and concepts** semantically, so you can catch contradictions before they go unnoticed. For **patterns and concepts**, you use `remind apply` to create them from episodes: ```bash remind apply << 'EOF' concept from=ep:11,ep:12 title="Retry-with-backoff for resilience" "Exponential…