"Learning Programming" matching MCP tools:

• list_coursesA

  RipostiqA

  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 also includes courses THEY authored (marked `mine`, with their `visibility`) — offer those alongside the catalog.

  ConnectorNo auth

• whenpeak_best_windowA

  WhenPeakA

  Find today's best time window for one kind of work, using the stored sleep history of the account this server is configured with. Returns a start and end time for the window and the projected capacity across it, tuned to the kind of work: analytical, creative, learning or administrative. Choose this tool when the user wants a slot for a task later today. Use whenpeak_performance_now for the current moment instead, and whenpeak_quick_predict when working from sleep the user describes rather than stored history. Requires WHENPEAK_API_KEY on the server and reads that one account's history, so it is only meaningful where the server runs with the user's own key. Without a key it returns a not_configured error rather than failing. Read-only and stores nothing, but each call counts against that account's monthly quota. Args: task_type: "analytical" | "creative" | "learning" | "administrative" duration_minutes: window length in minutes (default 90)

  ConnectorNo auth

• engram_proofA

  EngramA

  Audit adoption before a rollout or when checking whether the workspace is using memory and reporting outcomes. Takes no arguments. Returns JSON with memory-bank breakdowns, learning-loop activity, proof points and a benchmark checklist. Does not change knowledge or run a benchmark. Use engram_setup for onboarding and engram_recall for task knowledge. Consumes workspace daily call quota. OAuth: memory:read.

  ConnectorOAuth

• search_learning_pathsA

  VectreeA

  Search Vectree's curated learning paths — ordered sequences of diagrams that teach a subject from the ground up, one step at a time. Vectree explains how things work as zoomable, labelled schematics. A learning path strings a set of those diagrams into a syllabus, so a reader moves from the fundamentals of a subject to its harder parts in a deliberate order. Use this when the user wants to *learn*, *study* or *get started with* a whole subject. When they want one specific topic explained instead, use `search_diagrams` — that searches individual diagrams rather than sequences. Describe the subject in natural language; the search is semantic, so a full sentence works better than a bare keyword. Each result carries a slug — pass it to `get_learning_path` for the full ordered sequence. Only published paths are searched. Nothing is generated on demand, so a subject with no match simply has no path yet.

  ConnectorNo auth

• search_docsA

  Agent Docs ServerA

  Search the official documentation of Claude Code, Cursor, OpenAI Codex and MCP. Use it before answering any question about using, configuring or administering these products. Not for other products or general programming. If the answer could differ between products and the user hasn't said which one, ask. Returns one passage per page, with the page's one-line description and a relevance score; under ~0.5 means the docs probably don't cover it. One topic per call: split multi-part questions. Need more than the passage? Call read_section(url), or read_section(url, heading) for one of the passage's other_sections.

  ConnectorNo auth

• search_docsA

  Agent DocsA

  Search the official documentation of Claude Code, Cursor, OpenAI Codex and MCP. Use it before answering any question about using, configuring or administering these products. Not for other products or general programming. If the answer could differ between products and the user hasn't said which one, ask. Returns one passage per page, with the page's one-line description and a relevance score; under ~0.5 means the docs probably don't cover it. One topic per call: split multi-part questions. Need more than the passage? Call read_section(url), or read_section(url, heading) for one of the passage's other_sections.

  ConnectorNo auth

• revise_usability_testA

  TheySaidA

  Edits a usability test. Takes exactly one of `proposalId` (an unlaunched draft) or `projectId` (an already-launched test). Draft: plain-language `changes` and/or structured `edits` (add or remove tasks, questions and learning goals by index, swap personaIds, set `edits.audience`). Returns an updated plan under a new proposalId that replaces the previous one; nothing is launched. The number of AI testers changes only through `edits.audience.numTesters`. Launched test: only the audience can change (`edits.audience`, `edits.personaIds`). The change is saved to the project and echoed back as `audience`, and nothing runs until relaunch_usability_test. Tasks, questions and learning goals of a launched test cannot be edited; a new test is needed for that.

  Connector

  Destructive

  OAuth

• revert_to_versionA

  AIOProductOS MCPA

  Restore an earlier artifact version (F5) to current and return the now-current version: the existing current version is flipped to 'reverted' (kept for the learning signal) and the chosen version becomes current again. A write — not idempotent, since re-running reverts again. version_id is the version you want to RESTORE; get it from list_artifact_versions and never guess it. Optional reason is recorded.

  ConnectorNo auth

• view-hmr-unit-testsA

  hmrA

  The unit tests (code examples) for HMR. Always call `learn-hmr-basics` and `view-hmr-core-sources` to learn the core functionality before calling this tool. These files are the unit tests for the HMR library, which demonstrate the best practices and common coding patterns of using the library. You should use this tool when you need to write some code using the HMR library (maybe for reactive programming or implementing some integration). The response is identical to the MCP resource with the same name. Only use it once and prefer this tool to that resource if you can choose.

  ConnectorNo auth

• legends_get_gameA

  Legends of LearningA

  Fetches the full public detail for one Legends of Learning game by its numeric id (from legends_search_games). Returns the game's id, title, description, image, estimated_duration in minutes, type, grades served, teacher/student ratings, instructions, vocabulary, discussion questions, capability flags (supports_ipad, supports_tts, multi_language, saves_progress), lexile_level, the public url, and `learning_objectives` — the standards the game is aligned to, each with id, title, code, and standard_set. Example: {"game_id": 1445} returns that game, or an error result if no such game is publicly available.

  ConnectorNo auth

• get_course_infoA

  NTNU Courses (unofficial)A

  Everything about an NTNU course except exam logistics: credits, level, campus, language of instruction, prerequisites, mandatory activities, course content / learning outcomes, credit reductions ('studiepoengreduksjon'), which study programs the teaching is planned for, contacts, and any alert notices (e.g. 'no longer taught'). English text by default; pass language 'nb' for Norwegian. Omit year for the current study year. For exam dates, times, aid codes, and rooms use get_exam_info.

  ConnectorNo auth

• dev.code.languagesA

  apibaseB

  List all 71 available programming languages and their IDs for code execution. Common IDs: 71=Python 3.8, 63=JavaScript (Node.js), 62=Java, 54=C++ (GCC), 60=Go, 73=Rust, 51=C#, 46=Bash. Returns full list with compiler/interpreter versions (Judge0 CE)

  ConnectorNo auth

• get_subredditA

  RedditA

  Get posts from a REDDIT subreddit — r/LocalLLaMA, r/python, r/news. PREFER for "what are people posting in r/<sub>", "whats new on r/<sub> today", "top posts on Reddit this week". Sorted hot (default), new, top, rising, or controversial. For "top"/"controversial" pass a time window (day/week/month/year/all) — e.g. "top posts in r/programming this week". Returns post id, title, author, permalink, date, and a body snippet. (Vote score and comment count are not available via Reddit RSS.)

  ConnectorNo auth

• add_messages_to_sessionA

  RecallA

  Store specific messages the user wants kept, as they were said, so memory can learn from them. Send only those messages, never the conversation history. Creates the session and the speakers on first use; learning runs in the background, so do not wait for it. Pass idempotency_key when a retry is possible, so the same batch is never stored twice.

  ConnectorAPI key

• list_skillsA

  mcpA

  START HERE for any open-ended request. Lists the task playbooks this server supports — systematic learning from bookmarks, organising into themes, cleaning up, X-list intelligence, exporting data out, finding a half-remembered save, digests, and diagnosing sync. Each names when to use it; call get_skill for the exact tool sequence.

  ConnectorNo auth

• studies_create_draftA

  ZentrikB

  Use this when the user wants to create one unpublished, editable Study draft from an explicit learning need linked to an Idea or Initiative. An optional selected meeting excerpt is used only for generation and is not persisted. This never publishes, distributes, invites participants, records findings, or creates evidence.

  ConnectorOAuth

• gate_sync_declarativeA

  Odile GateA

  Make a Gate project match an odile.yaml: creates the project (if no project_id) and missing apps and approvers, applies run mode, loop and learning settings and alerts. Never revokes or deletes; differences it cannot apply (an app's routes or rate limit) come back as drift. dry_run lists the steps without changing anything. New keys are shown once.

  ConnectorNo auth

• tags-manageA

  hjarniA

  Rename, merge, or delete a tag — the cleanup tools for the tag list (this operates on the tag itself, unlike notes-update which only edits one note's tags). Required: action ('rename'|'merge'|'delete') and the tag to act on via name (string, case-insensitive) or tag_id (integer). For 'rename' also pass new_name. For 'merge' also pass the destination via target_name or target_id: every note on the source tag is moved onto the destination and the source tag is deleted — ideal for collapsing duplicates like 'machine learning' into 'machine-learning'. If target_name names a tag that doesn't exist yet, it's created, so you can merge straight into a clean canonical name without creating it first. 'delete' removes the tag from all its notes and deletes it; deleting a name that doesn't exist succeeds as a no-op (already_absent: true), so it's safe to retry. Merge and delete are destructive and cannot be undone; check tags-list first.

  Connector

  Destructive

  OAuth

• get_nowA

  Cameron Rye Portfolio MCP ServerA

  Return what Cameron is currently working on, learning, building, reading, and up to in life — the live /now page sections.

  ConnectorNo auth

• get_my_briefingA

  welcomeA

  Your daily briefing at The Balanced Investor Club — a read on your own activity: morning brief, journal counts, the instruments you follow, mood highlights, activity, and your learning journey. A mirror, never advice.

  ConnectorNo auth

• explain_optimizationA

  SCModelingA

  Reference text on supply-chain network optimization — mixed-integer programming (MIP), the structure of decision variables and constraints, the objective function for landed-cost minimization, and the common problem classes (facility selection, sourcing, flow constraints, multi-period, BOM/production, multi-objective). Also covers when to reach for optimization vs simulation. Pure static text — no engine call, deterministic output. Use this when the user asks a conceptual 'how does network optimization work' question. ChiAha's AMOS optimizer (open-source, Odin, GLOP/CBC via OR-Tools) powers the Tariff and Coffee Co-pack demos on the sandbox.

  ConnectorNo auth