Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Create, personalize and deliver branded workouts and programs from any AI assistant.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Funktioniert in Claude im Web, auf dem Desktop und auf dem Handy:
https://mcp.hyperhuman.cc/mcpFühre das in deinem Terminal aus
claude mcp add --transport http hyperhuman https://mcp.hyperhuman.cc/mcpIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"hyperhuman": {
"url": "https://mcp.hyperhuman.cc/mcp"
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"hyperhuman": {
"type": "http",
"url": "https://mcp.hyperhuman.cc/mcp"
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
ChatGPT verbindet sich nur mit Servern im Internet:
https://mcp.hyperhuman.cc/mcpMenünamen können sich je nach Tarif und mit der Zeit leicht unterscheiden.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Tool-Namen und -Beschreibungen genau so, wie der Server sie am 6. Nov. 2026 gemeldet hat. Geschrieben hat sie der Entwickler, nicht wir; wir zeigen sie als reinen Text.
get_integration_planReturns an integration strategy and step-by-step plan for Hyperhuman workouts or programs: embed (iframe), stream videos (VOD export), or custom player (API + playlist). Use when the user asks how to integrate Hyperhuman or what integration options exist. Pass platform (web/mobil
list_sample_workoutsReturns a workout carousel for sample-workout prompts. When the user is connected via OAuth, lists up to 8 team workouts through the Internal API (Bearer token only — no Content API key required). When not connected, returns up to 6 curated guest samples with embedDemoUrl. Use wh
get_workout_detailsReturns workout metadata, preview assets, and summary. Use when the user selects a workout or asks for details about a specific workout. sample-* ids return a curated sample detail (no auth). Connected team workout ids use the Internal API (same data as get_team_workout). Other o
get_workout_playlistReturns playlist segments with timing and media pointers (progressive MP4/M4A URLs, typically ~7 days). sample-* ids return a curated sample playlist (no auth, no live media URLs). Connected org ids use the Content API when the team has API entitlement. Use when the user wants to
get_embed_code_samplesReturns static copy-paste code templates for workout embeds (keyHandshake iframe), program page embeds, custom player JavaScript, or Content API cURL snippets. All samples contain only placeholder values (YOUR_ORG_ID, YOUR_API_KEY) — no real credentials are fetched or transmitted
list_team_workoutsReturns workouts for the authenticated user's team via Internal API. Use when the user asks to see my team's workouts, my team workouts, or their organization workout library. Requires OAuth. Not for curated sample workouts or guest embed demo (use list_sample_workouts).
get_team_workoutReturns full details of a workout from the team. Use when the user selects a workout or asks for details about a specific workout.
list_team_programsReturns workout programs (collections) for the authenticated user's team. Use when the user asks to see programs, training plans, or workout collections.
get_team_programReturns full details of a workout program from the team. Use when the user selects a program or asks for program structure.
list_team_goalsReturns fitness goals available for programs. Use when creating or generating programs to get valid goal IDs.
list_workout_categoriesReturns workout categories for workouts. Use when creating or updating workouts to get valid category_ids.
list_muscle_groupsReturns muscle groups for exercises. Use when updating exercise metadata or filtering exercises.
list_equipmentReturns equipment for exercises. Use when updating exercise metadata or filtering exercises.
get_team_usageReturns usage quotas for the authenticated team (e.g. social drop export count and limits). Use when the user asks about usage, quotas, or limits.
get_session_summaryReturns team name, plan label, and usage limits for the connected account. Use only when the user explicitly asks about their team, plan, or usage quotas.
get_api_usage_statsReturns API key usage statistics for the current user's team. Use when the user asks about API usage, request counts, or rate limits.
list_team_dropsReturns social drops (videos, covers, copy) for the team. Use when the user asks about drops, social assets, or ready-to-download content.
get_dashboard_summaryReturns dashboard summary: latest created workouts with stats and ready-to-download items. Use when the user asks about dashboard, recent workouts, or content ready for download.
create_dropCreates a social drop from an exercise, exercise group, workout, or program. Use when the user wants to create social media content from existing content.
regenerate_drop_copyRegenerates AI copy pack (hook, caption, hashtags, CTA) for a drop. Use when the user wants to refresh or improve the social copy.
regenerate_drop_coverRegenerates AI cover image for a drop. Use when the user wants a new cover for the social asset.
export_dropExports drop assets for a channel (video URL, cover URL, copy pack). Use when the user wants to download assets or prepare a drop for external publishing.
generate_programGenerates an AI training program using team workouts. Use when the user wants to create a multi-week program from their workout library.
create_workoutCreates a workout from exercise and rest instances. Use when the user wants to build a custom workout. Provide either exercise_map (ordered array of instance IDs from create_exercise_instance and create_rest_instance) or instances (raw instance objects). Workout cannot start or e
update_workoutUpdates an existing workout. Use when the user wants to change workout name, description, difficulty, visibility, or exercise structure. When only partial fields are provided (e.g. name), the current workout data is fetched and merged automatically.
create_programCreates a workout program from team workouts. Use when the user wants to organize workouts into a multi-week program. Requires goal_ids (1-2) and workout_ids (min 2).
update_programUpdates an existing program. Use when the user wants to set duration, workouts per week, or edit program metadata. When updating, provide full program data (goal_ids, workout_ids, visibility, difficulty) from get_team_program and merge your changes.
update_exercise_groupUpdates an exercise group. Use when the user wants to change name, exercises, rounds, or rest time.
update_exercise_metadataUpdates exercise metadata (name, muscle groups, categories, equipment, skill level). Use when the user wants to fix or improve exercise tagging. Only team-owned exercises can be updated; stock exercises are read-only. Provide at least one field to update besides exercise_id.
list_stock_programsReturns platform stock programs (publisher programs). Use when the user wants to browse or clone stock programs.
clone_stock_programsClones stock programs to the user's team. Use when the user wants to add publisher programs to their library.
update_dropUpdates a drop title or channel preset. Use when the user wants to change drop display title or default export channel. For copy changes use regenerate_drop_copy.
list_team_exercisesReturns exercises from the team library. Use when the user wants to browse exercises, find exercises for workouts, or manage the library.
get_team_exerciseReturns full details of an exercise from the team library. Use when the user selects an exercise or asks for exercise details.
create_exercise_instanceCreates an exercise instance with duration/reps, pace, weight, RPE. Use when building a workout manually - create instances for each exercise, then pass instance IDs to create_workout. Stock and team exercises can be used directly via exercise_id.
create_rest_instanceCreates a rest/break instance for use between exercises in a workout. Use when building a workout manually - create rest instances, then include their IDs in create_workout exercise_map. Workout cannot start or end with rest.
create_exercise_groupCreates an exercise group (circuit or sets). Use when the user wants to group exercises for circuits or micro-workouts. Requires at least 2 exercise IDs.
generate_video_clipGenerates an AI exercise video from a trainer photo (CloneMotion). Use when the user wants to create exercise videos without filming. Before calling, ensure you have the target exercise and image source (upload URL or saved trainer image ID); optionally ask for specific video req
get_video_generation_statusReturns status and result of a CloneMotion video generation job. Use when the user wants to check if a generated video is ready or view the generated variants. Generation can take a few minutes; if status is pending or running, ask the user to check again after waiting.
generate_workoutGenerates an AI workout via Content API. Use when the user wants to create a personalized workout on-the-fly. Returns workout structure (not persisted to team library by default).
recommend_workoutsReturns ranked workout recommendations from the organization library (up to 12 workouts in the tool response; optional limit up to 20 is sent to the API). Use when the user wants instant suggestions based on profile (faster than generate).
adapt_workoutAdapts an existing workout for a user profile. Use when the user wants to customize a workout (duration, difficulty, equipment) without generating from scratch.
recommend_plansReturns ranked program recommendations from the organization library (up to 12 programs in the tool response; optional limit up to 20 is sent to the API). Use when the user wants instant program suggestions.
adapt_planAdapts an existing program for a user profile. Use when the user wants to customize a program.
health_checkReturns MCP server readiness status with a fixed ready message. Use when the user asks if the Hyperhuman app is working, reachable, or connected.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026
Die Registry nennt kein Quell-Repo, deshalb können wir den Herausgeber (hyperhuman.cc) nicht dem Code zuordnen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Antwort in 239 ms (HTTP 200)
Keine Anmeldung nötig
Wir haben 45 Tool-Beschreibungen gelesen und keine versteckten Anweisungen an die KI gefunden
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 2 von 3 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft in der Cloud des Entwicklers. Du verbindest dich übers Internet, ohne etwas zu installieren, aber was du sendest, läuft über die Server des Entwicklers.
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.1.0) kam vor 5 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Er verbindet sich per URL, also funktionieren auch Apps, die Remote-MCP-Server akzeptieren, zum Beispiel ChatGPT im Entwicklermodus.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, FlyDocs
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Spec-driven development workflow: your agent works issues, sessions and the status lifecycle.
Keine README im Repo gefunden