Honcho
Memory that reasons: continual learning for stateful agents. Better context, fewer tokens.
作者提供的说明(英文原文)
Courses that argue back: learn adaptively, build real work, then defend it to an AI stakeholder.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
适用于网页版、桌面版和手机版 Claude:
https://ripostiq.com/mcp在终端中运行这条命令
claude mcp add --transport http ripostiq https://ripostiq.com/mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"ripostiq": {
"url": "https://ripostiq.com/mcp"
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"ripostiq": {
"type": "http",
"url": "https://ripostiq.com/mcp"
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
ChatGPT 只能连接互联网上的服务器:
https://ripostiq.com/mcp菜单名称可能因套餐和版本不同而略有差异。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
工具名称和描述与服务器在 2026年11月10日 报告的完全一致。这些内容由作者撰写,不是我们写的;我们以纯文本形式显示。
loginClaude 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.
whoamiReturn the current logged-in user (via OAuth bearer or an auth_token).
get_entitlementsList the logged-in account's entitlements across courses (OAuth bearer or auth_token).
get_lessonFetch a module's lesson content. Free module is open; paid modules require an active entitlement. Returns {locked, teaser, checkout_url} when not entitled.
list_coursesList 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 logg
begin_courseStart 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.
roastFree '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/architectu
interview_prepFree '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
list_interviewsList 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 want
start_interviewBegin 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 ret
teach_sectionGet 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.
run_bossGet 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_styl
daily_drillThe 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 h
start_examStart 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 / locke
submit_examScore 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-quest
get_outlineFull 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.
mark_progressRecord 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=...).
get_recapResume briefing for a returning learner — what they've covered, mastery levels, strong/weak topics, and recall questions to reactivate memory. Call at session start.
get_progressReturn 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).
recall_questionsReturn spaced-recall questions drawn from the account's completed modules.
list_artifactsList the learner's saved Library artifacts (titles + metadata, newest first). Use at session start (with get_recap) to reference prior work and continue seamlessly.
get_artifactFetch 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.
submit_artifactSubmit 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.
get_certificateRipostiq 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/ .
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月10日
注册中心没有列出源代码仓库,因此无法将发布者(ripostiq.com)与代码对应起来
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
在 210 毫秒内响应(HTTP 200)
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已读取 24 个工具描述,未发现针对 AI 的隐藏指令
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 3 项适用的基础检查中通过了 2 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(1.0.0)于3个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:Honcho, ShipSwift, Pm Claude Skills
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Memory that reasons: continual learning for stateful agents. Better context, fewer tokens.
1310 professional Agent Skills + workflow recipes — searchable & fetchable over MCP.
仓库中没有找到 README