MCP servercom.ripostiq/ripostiq

Start a course. Returns the tutor protocol, intake guidance, and the module map. Call this first, run the intake, then call teach_section to teach Module 1.

The two-minute drill — today's spaced-recall question + the learner's day streak. Call it to fetch today's question (deterministic per day, drawn from modules they've started); aft

Fetch a saved Library artifact's full content (by id, or by key+course). Use to pull a prior deliverable forward and build on it in a new chat.

Ripostiq certificate status. Pass `module` for that module's certificate (earned when its boss battle is passed); omit it for the course certificate (earned when EVERY module's bos

List the logged-in account's entitlements across courses (OAuth bearer or auth_token).

Fetch a module's lesson content. Free module is open; paid modules require an active entitlement. Returns {locked, teaser, checkout_url} when not entitled.

Full course outline — every module + its section titles — so the learner can pick ANY module/section to start, in any order. Marks locked modules and their progress.

Return the learner's progress for a course — the raw doc plus a display-ready summary (per-module sections done/total, boss status, overall percent, current position), and wind_dow

Resume briefing for a returning learner — what they've covered, mastery levels, strong/weak topics, and recall questions to reactivate memory. Call at session start.

Free 'Mock interview' — a realistic, calibrated interview for a role. `jd_or_skill` is the job description (paste it) or the skill/role to interview against; `role` and `experience

List the learner's saved Library artifacts (titles + metadata, newest first). Use at session start (with get_recap) to reference prior work and continue seamlessly.

List every available Ripostiq course (no login needed). Call this FIRST when a user wants to browse or start learning. Each course has a free Module 1 anyone can start immediately

List the curated Interview-Prep topics (e.g. 'Agentic AI in Production'). Each is a realistic, adaptive mock interview on a fixed topic — concept→scenario question pairs across sev

Claude Code plugin login only (auth_token flow). On the web/desktop connector, identity comes from the connector's OAuth approval — do NOT ask the user to type their email/password

Record the learner's progress server-side (shows on their account + syncs across devices). Call when a section is genuinely completed (section_id), or after a boss battle (boss='pa

Return spaced-recall questions drawn from the account's completed modules.

Free 'Roast my work' — a single tough-but-fair stakeholder grilling of ANY artifact the user pastes (PRD, architecture, code, pitch, resume, plan, essay…). No login or course neede

Get the module's boss-battle simulation + how to run it (in-character, real stakes, earned PASS). Gated like lessons. `difficulty` dials the intensity — 'friendly' (supportive coac

Start the course's SCORED PRACTICE EXAM — a full, blueprint-aligned multiple-choice mock that returns a scaled score against the real pass line, a per-domain breakdown, and rationa

Begin a curated Interview-Prep session on a fixed topic. `interview` is the topic id from list_interviews (e.g. 'agentic-ai-in-production'); `role`/`experience` calibrate difficult

Submit a lab deliverable. Stores it in the learner's Library (type='deliverable') and returns the module rubric so it can be reviewed against the bar. Call get_review next. For gen

Score a practice exam started with start_exam. `answers` maps each question id to the learner's chosen letter, e.g. {"q001": "A", "q002": "C"}; unanswered questions score as incorr

Get one lesson section's content + the teaching protocol for it. Free module is open; paid modules require an active entitlement (returns {locked, teaser} if not). Teach it socrati

Return the current logged-in user (via OAuth bearer or an auth_token).