mhn-project-working-memorylisted

# MHN project working memory (Cursor) ## Idea Associative memory lives in a **JSON file on disk** (not in chat). Any agent with the same MCP config reads and updates the same store, so memory is **swappable between agents** and survives new conversations. ## Setup (once per machine) 1. Create the MCP server venv: see `mcp-server/README.md` (`pip install -e .` inside `mcp-server/`). 2. Copy `.cursor/mcp.json.example` to `.cursor/mcp.json` in this repo (or merge the `hopfield-memory` entry into user-level MCP config). 3. Replace placeholder paths with **absolute** paths to `mcp-server/.venv/bin/python` and `mcp-server/server.py`, or use `${workspaceFolder}` if your Cursor build expands it. 4. Set `HOPFIELD_STATE_PATH` to a path **inside the project** (default example: `.mhn/working-memory.json`). Enable `HOPFIELD_AUTO_SAVE=true` so `store` / `store_negative` persist immediately. 5. Restart MCP / Cursor so the server picks up env vars. The bundled `.cursor/mcp.json.example` sets `HOPFIELD_ENCODER` to `sentence_transformer`; install the parent package with semantic extras into the **same venv** as the MCP server (`./mcp-server/.venv/bin/pip install -e ".[semantic]"` from repo root), **or** change that env var to `random` if you want no extra dependencies (weaker recall). Use `sentence_transformer` (or better encoders) for semantic recall; `random` is fine only for exact-token overlap demos. ## Agent workflow 1. **`working_memory_status`** — Confirm `state_path`, `auto_sav