MCP server

Ripostiq Official

com.ripostiq/ripostiq

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Courses that argue back: learn adaptively, build real work, then defend it to an AI stakeholder.

Working at last checkVerified publisher: ripostiq.comAbout 4,033 tokens per request once connected24 toolsDescription tries to instruct AI agents

Website

https://ripostiq.com/mcp

At a glance

Type: MCP server
Publisher: ripostiq.com (verified by the MCP Registry)
Status: Working at last check
Tools: 24
Token cost: About 4,033 tokens per request
Sets up in: Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok
Last checked: 26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to Cursor Add to VS Code VS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http ripostiq https://ripostiq.com/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.ripostiq]
url = "https://ripostiq.com/mcp"

Gemini CLI

{"mcpServers":{"ripostiq":{"httpUrl":"https://ripostiq.com/mcp"}}}

Cursor

{"mcpServers":{"ripostiq":{"url":"https://ripostiq.com/mcp"}}}

VS Code

{"servers":{"ripostiq":{"type":"http","url":"https://ripostiq.com/mcp"}}}

Antigravity

agy mcp add ripostiq https://ripostiq.com/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"ripostiq","server_url":"https://ripostiq.com/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"ripostiq","server_url":"https://ripostiq.com/mcp"}

Tools

begin_course ~114 tokens
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.
daily_drill ~177 tokens
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); after they answer and you reveal it, call again with done=true to log it and bump the streak. A daily habit: one question,
get_artifact ~157 tokens
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.
get_certificate ~168 tokens
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 boss is passed). Both are viewable at /certificate and publicly verifiable at /verify/<code>.
get_entitlements ~81 tokens
List the logged-in account's entitlements across courses (OAuth bearer or auth_token).
get_lesson ~144 tokens
Fetch a module's lesson content. Free module is open; paid modules require an active entitlement. Returns {locked, teaser, checkout_url} when not entitled.
get_outline ~116 tokens
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.
get_progress ~142 tokens
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_down coverage (which modules have their cheatsheet + session summary saved).
get_recap ~116 tokens
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.
interview_prep ~262 tokens
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` (e.g. 'senior backend engineer', '5 years') calibrate difficulty; `focus` narrows it (e.g. 'system design'). No login
list_artifacts ~156 tokens
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_courses ~174 tokens
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 via begin_course(course) → teach_section. Returns the `course` id to pass to other tools. For a logged-in learner this a
list_interviews ~138 tokens
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 several areas — that ends in a candid scorecard. No login or course needed. Call this when someone wants to prep for an int
login ~136 tokens
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 into the chat; direct them to the connector's 'Log in with Ripostiq' or ripostiq.com instead.
mark_progress ~226 tokens
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='passed'/'failed', boss_attempt=true), or on a lab status change (lab=...).
recall_questions ~94 tokens
Return spaced-recall questions drawn from the account's completed modules.
roast ~256 tokens
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 needed. `work` is the artifact (or a solid description); `kind` optionally hints the type (prd/architecture/code/pitch/strate
run_boss ~249 tokens
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 coach), 'standard' (default), or 'brutal' (relentless, skeptical, high bar) — and optional `persona_style` sets a flavor (e.
start_exam ~222 tokens
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 rationale for every question. Login + entitlement gated like the paid capstone (returns needs_login / locked if not). Returns a
start_interview ~274 tokens
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 difficulty. LOGIN REQUIRED (free in the current beta, like a course): if the learner isn't logged in this returns needs_login — a
submit_artifact ~196 tokens
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 general note-taking use save_artifact instead.
submit_exam ~201 tokens
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 incorrect. Returns the scaled score, PASS/FAIL vs the pass line, a per-domain breakdown, and the per-question rationale for re
teach_section ~161 tokens
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 socratically, then call again with section_index+1 to advance.
whoami ~73 tokens
Return the current logged-in user (via OAuth bearer or an auth_token).

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