Categories › AI & Agents › Agent memory & context
The context marketplace: expert guided journeys your assistant runs step by step.
Remote server: your requests and data go to capxule.ai. Claude Code: claude mcp add --transport http capxule https://capxule.ai/mcp · Claude app: Settings → Connectors → Add custom connector.
The tools this server listed when we connected to it, in its own words.
find_journey — Use when the user wants a guided, step-by-step journey on a topic, a skill or an exam. Searches the published journeys and returns up to thrlist_journey_categories — Use when the user asks what kinds of journeys are available. Returns each category slug, a readable label, the number of journeys in it and browse_journeys — Use when the user wants to look through the journeys, optionally within one category (a slug from list_journey_categories). Returns a page oopen_journey — Use when the user chooses a journey to start or continue. Opens it, or resumes the user's session for it, and returns the session contract: take_journey_step — Use for every step after open_journey. Sends the user's choice and returns the next step: `answer`, `statement`, numbered `options` with idsget_journey_progress — Use when the user asks where they are in a journey, how far they have come or how much is left. Returns the current stop, visited and remaincreate_takeaway — Use when the user asks for a summary to keep. Composes a markdown takeaway from this journey session: what the user asked, the key points anget_resume_link — Use when the user wants to continue the journey later, on the website or in another assistant. Returns a resume link and a short resume coderestart_journey — Use only when the user explicitly asks to start a journey over, after confirming with them. Returns to the first step and clears the visitedNot tested by KitScout yet. When our harness runs it, pros, cons and the tasks we tried appear here, with the date and evidence.