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You will go from a fresh account to a working, correctable memory in about ten minutes. This page is the generic path; the per-tool setup detail lives in the connect guides. Prerequisites:
  • An xysq account. Sign up at app.xysq.ai.
  • One AI tool that speaks MCP. Claude, Claude Code, Cursor, ChatGPT, and Windsurf all work. No MCP client handy? Link WhatsApp instead and text your memory from your phone.
1

Connect your first AI tool

Pick your tool in the connect guides and follow its steps. The in-app guide at app.xysq.ai walks the same steps with your key and config pre-filled; the result is the same either way: the xysq MCP server is wired into your tool.Verify it worked: ask your tool “are you connected to xysq?”. It should call userinfo and answer with something like “Connected. 0 items in memory staging.”
2

Push your first context

Work in your tool normally for a bit, then say: “Save this session to xysq.” The tool calls push_context with the transcript, and the call returns immediately. The engine does everything else server-side: extraction, deduplication, structuring, indexing.
The transcript goes in verbatim, turn by turn, not summarized. Summarizing destroys the details the engine extracts from (exact numbers, names, file paths). The server decides what is durable, not the tool. Re-pushing identical content is safe; the server dedupes it.
3

See it in your vault

Open your vault at app.xysq.ai.
  • The Sources tab shows the raw push, stored byte for byte. Nothing derived from it edits it: no distill, no page rewrite. Correcting it is a deliberate act, by you here or by an agent through the SDK, and the earlier version stays in that source’s History rather than being overwritten.
  • The Pages tab shows the distilled pages the engine built from it. They appear once the background worker has run, and every fact on a page cites the source it came from.
Retrieval is fresher than the pages. The verbatim text is indexed for search as soon as the background worker picks the push up; the distilled page needs a model pass, so it lands later. pull_context searches both, so a fresh push is findable before its page exists.
4

Pull it back in a new session

Start a fresh session, in the same tool or a different connected one, and ask about the topic: “What did we decide about the migration?” The tool calls pull_context with a plain-words query and gets ranked context back. One memory, every connected tool.
5

Correct something and watch it apply

Find a fact in your pages that is wrong or stale. Tell any connected tool the correction and have it push it, for example: “Correction for xysq: we deprecated the v2 endpoint in March, everything routes through v3 now.”The engine treats this as superseding evidence. On its next run over your vault it closes the old fact, rewrites every page that carried it, and stops serving the closed fact. Ask about it again: the answer serves the corrected state. That is the loop the whole product is built on. Correct once, and it improves.A run that cannot be applied cleanly is refused as a whole batch and retried, so nothing lands half-changed.

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Where next

Connect guides

Per-tool setup for Claude, Claude Code, Cursor, ChatGPT, Windsurf, and more.

Concepts

The context lake, context graphs, and how the engine works underneath.

MCP reference

Exact parameters and responses for all four tools.

WhatsApp

Link your number and text your memory. No MCP client needed.