MarsNMe gives AI agents persistent memory across sessions. Two tiers: short-term context (auto-expiry) and long-term semantic recall via Jina embeddings + pgvector. 13 MCP tools. Multi-profile isolation. Works with Claude Desktop, Cursor, Warp. Apache 2.0, self-hosted. One npx command to start.
Hey PH — Mars here, one of the builders behind MarsNMe.
The frustration that started this: I was using Claude and Cursor daily for real work, and every session started
from zero. I'd re-explain the same project context, the same constraints, a dozen times. It felt like working with
a colleague who had perfect skills but permanent amnesia.
System prompts help, but they're static. They don't capture what actually happened last Tuesday, or that I changed
my mind about the architecture.
So we built MarsNMe — a memory backend that any MCP-compatible agent can talk to. Two Supabase tables, a local HTTP
gateway, and Jina v3 embeddings for semantic retrieval. pgvector keeps recall fast as memory grows.
The multi-profile design came from a real need — we run several agents and didn't want them sharing memory.
Schema-level separation, not just a filter.
Apache 2.0, fully self-hosted. We're a small team from Macau. Happy to answer any questions!
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