Hi all, Edward here, I build Mnemoverse.
It is a hosted memory API your agent reaches over MCP. You write a fact once (a preference, a decision, a lesson learned) and recall it in later sessions and from other tools: the same memory works in Cursor, Claude Code and VS Code with one key, and in ChatGPT via a Custom GPT action.
How it differs from the local-first memory servers shared here (Recall, Mnemosyne, PMB are all good projects): those keep everything on your machine, which wins on privacy and latency. Mnemoverse is the managed, cross-tool option, and it does not just store vectors: each write gets an importance score, related concepts link up, and when you report that a recalled memory actually helped, that feedback re-ranks future recall. So it learns which memories are worth surfacing.
Setup in Cursor: Settings → MCP, then
json {"mcpServers": {"mnemoverse": {"command": "npx", "args": ["-y", "@mnemoverse/mcp-memory-server@latest"], "env": {"MNEMOVERSE_API_KEY": "mk_live_YOUR_KEY", "MNEMOVERSE_API_URL": "https://core.mnemoverse.com/api/v1"}}}}
Free key at console.mnemoverse.com (1,000 queries/day, no card). MCP server and Python SDK are MIT; the engine is hosted. There is a research paper behind the memory model if you like that sort of thing: arXiv 2603.08965.
Honest caveat: if you want fully local and private, pick one of the local-first servers above. If you want one memory across your tools without running anything, that is what this is for. Happy to answer anything.