I gave my AI agents a shared memory via MCP — here's how

Most people don't know **MCP (Model Context Protocol)** yet. It's a standard that lets AI agents use tools — the same `remember()` and `recall()` that works in Hermes also works in Claude Code, Cursor, Cline, and every other MCP-compatible agent. No per-agent plugins. No custom APIs. One protocol, one memory. **Nexus Memory** is an MCP-native memory server. You point any MCP agent at it, and suddenly your agents share context: Agent A: "User prefers dark mode, tailwind, and short commit messages." Agent B (different tool, minutes later): reads that memory. Adapts instantly. **What you get (10 MCP tools):** \- `remember` / `recall` / `forget` / `update` — CRUD via MCP \- `health` / `check_update` / `do_update` — ops \- `subscribe` / `unsubscribe` / `list_subscriptions` — webhooks for memory events **MCP agents that work with it out of the box:** Hermes · Claude Code · Cursor · Kilo Code · Cline · Codex · OpenClaw · GitHub Copilot **Why not just a vector DB?** Because agents need more than `SELECT * FROM vectors ORDER BY similarity`. They need categories (fact vs belief vs temp), drift detection for outdated info, source verification, and access control. Nexus wraps all that into MCP tools — drop-in, no glue code. >*"Not just an MCP addon — a feature-rich, standalone memory system."* — Perplexity, 9.4/10 >*"Sets a new standard for agent memory management."* — Gemini, 9.5/10 **Stack:** Python, Qdrant (self-hosted), FastAPI, MCP stdio. 379 tests. MIT. 6 embedding providers. Want to try it? Search GitHub for Neboy72/nexus-memory. Feedback welcome.