Categories › AI & Agents › Agent memory & context
Personal memory layer: files, notes, messages, tasks and email, semantically indexed.
Remote server: your requests and data go to mcp.cortexplus.io. Claude Code: claude mcp add --transport http cortexplus https://mcp.cortexplus.io/mcp · Claude app: Settings → Connectors → Add custom connector.
The tools this server listed when we connected to it, in its own words.
search — Search the user's CortexPlus memory and return ranked matches. Use this to find what the user has stored before answering from memory. Healtfetch — Retrieve the full content of one CortexPlus memory item by id, as returned by search. Health data (`saude` tag) is only included when the usrecall — Build a context block from the user's CortexPlus memory: the passages that answer a question plus their graph neighbours, already formatted remember — Store a note in the user's CortexPlus memory so future conversations can recall it.memory — Save a memory in CortexPlus. CortexPlus decides whether it is a note, task, or reminder and extracts the client.tasks — List open CortexPlus tasks and reminders, optionally filtered by client.save_context — Save a handoff summary of this conversation to the user's CortexPlus memory so it can be resumed later in another AI platform. Write the sumresume — Load a previously saved CortexPlus context pack to resume work started in another AI conversation.context_packs — List saved CortexPlus context packs, optionally filtered by AI platform.signup — Create a CortexPlus account, or begin signing in to an existing one, so this conversation can use CortexPlus as the user's long-term memory connect — Complete the CortexPlus connection with the 6-digit code the user received by email after signup. Ask the user for the code, then call this Not tested by KitScout yet. When our harness runs it, pros, cons and the tasks we tried appear here, with the date and evidence.