Clude Memory MCP

# Clude Memory MCP MCP server exposing a 4-tier cognitive memory architecture inspired by Stanford's Generative Agents (Park et al. 2023). ## Tools ### `recall_memories` Search the memory system. Returns scored memories ranked by relevance, importance, recency, and vector similarity. - `query` — text to search against memory summaries - `tags` — filter by tags - `related_user` — filter by user/agent ID - `memory_types` — filter by type: `episodic`, `semantic`, `procedural`, `self_model` - `limit` — max results (1-20, default 5) - `min_importance` — minimum importance threshold (0-1) ### `store_memory` Store a new memory. Memories persist across conversations, decay over time if not accessed, and get committed to Solana. - `type` — `episodic` (events), `semantic` (knowledge), `procedural` (behaviors), `self_model` (identity) - `content` — full memory content - `summary` — short summary for recall matching - `tags` — tags for filtering - `importance` — importance score 0-1 - `source` — origin identifier (e.g. `mcp:my-agent`) ### `get_memory_stats` Get statistics: counts by type, average importance/decay, dream session history, top tags. ### `get_market_mood` Get current market mood and price state (no LLM call). ### `ask_clude` Ask Clude a question and get an in-character response. Calls Claude API. ## Setup ```bash npm install clude-bot ``` Requires a Supabase project with the schema from `supabase-schema.sql`. Set `SUPABASE_URL` and `SUPABASE_SERVICE_KEY` environment variables. ## Architecture - **4-tier memory**: episodic (7%/day decay), semantic (2%/day), procedural (3%/day), self_model (1%/day) - **Hybrid retrieval**: pgvector cosine similarity + keyword matching + tag scoring - **Dream cycles**: consolidation, reflection, emergence — every 6 hours - **On-chain commitment**: SHA-256 hashed memories committed to Solana via memo transactions - **Granular decomposition**: per-fragment embeddings for precise sub-memory retrieval ## License MIT