Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Turns the training evidence you already have into a decision about today's session.
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.
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Die .mcpb-Datei des Entwicklers herunterladen
Der Link führt zur Datei des Entwicklers selbst; wir hosten sie nicht und verpacken sie nicht neu. Öffne die Datei, dann installiert Claude Desktop sie.
Führe das in deinem Terminal aus
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.
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.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
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.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
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
Der Registry-Name wurde mit dem GitHub-Konto henryyeh182 bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 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 auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.5.8) kam vor 2 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du MCPB auf deinem Computer.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, Dialyne
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.
Real phone calls in France for AI agents: dial +33 numbers, menus, hold, AI disclosure.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
Pacevera is a deterministic fitness decision engine exposed through the Model Context Protocol (MCP). It receives normalized training and health evidence supplied by the calling AI host, evaluates recovery and training constraints, and returns a structured decision.
The primary operation is to evaluate an existing scheduled session. A decision describes the change from the scheduled session to the resulting session:
scheduled session (from) -> resulting session (to)
Each decision includes the relevant evidence, applied rules, confidence, signal coverage, and limitations.
Pacevera provides the following capabilities:
keep, adjust, substitute, defer, and advance.Pacevera does not connect to these providers on behalf of the user. The calling host must obtain and normalize provider exports or API responses before passing them to an MCP tool.
AI host
└─ Collects the user's question and evidence └─ MCP server / desktop extension ├─ Evidence normalization ├─ Fitness-state calculation ├─ Training-load calculation ├─ Deterministic rule evaluation ├─ Decision and plan operations └─ Structured result: Decision / Action / Reason
The AI host is responsible for interpreting the user's request, collecting evidence, selecting tools, and presenting the result. Pacevera performs the calculations and rule evaluation; it does not call a model to generate a decision. Given the same code, rule set, and input, the result is deterministic.
| Type | Description |
|---|---|
| Recommendation | A training suggestion generated without a required prior session or plan. |
| Decision | A traceable change applied to an existing scheduled session or plan. |
decide_session requires scheduledSession to establish the prior state. If no scheduled session is provided, the tool returns no_scheduled_session rather than creating a session. Use generate_plan when a plan is required.
Decision output follows five layers:
Evidence -> Fitness State -> Decision -> Action -> Reason
Decision intent and resulting action are separate fields. The same intent may produce different actions depending on the user's equipment, available time, injuries, and scheduled session.
| Tool | Description |
|---|---|
assess_fitness_state | Returns recovery, readiness, muscle-group fatigue, and training-load state. |
decide_session | Evaluates a scheduled session and returns the resulting session. |
decide_exercise_substitution | Selects a replacement movement subject to injury and equipment constraints. |
generate_plan | Generates a periodized training plan. |
preview_adjust_plan | Returns a deterministic patch and diff for a caller-owned plan. |
commit_adjust_plan | Validates the plan version and applies a caller-owned patch. |
| Tool | Description |
|---|---|
get_evidence_coverage | Reports available and missing evidence signals. |
explain_decision | Returns the process-local rule and source trace for a previous decision. |
submit_outcome | Accepts an observed outcome for a prior case; storage is bounded and local to the configured environment. |
search_exercises / get_exercise | Queries the exercise catalog and graph relationships. |
search_workouts / get_workout | Queries structured workout content. |
get_user_profile | Returns caller-supplied user constraints and training settings. |
get_training_history / get_training_context | Returns training history and related context. |
Evidence is supplied by the calling host. It may include recovery measurements, vendor-computed assessments, completed workouts, scheduled sessions, goals, and constraints.
Important input rules:
signalCoverage and may lower confidence.A typical decide_session response has this shape:
{
"decision": { "type": "adjust", "intent": "reduce_today_intensity" }, "action": { "from": { "focus": "Tempo Run", "durationMinutes": 50, "intensity": "high" }, "to": { "focus": "Moderate run", "durationMinutes": 50, "intensity": "moderate" }, "changed": ["focus", "intensity"] }, "confidence": "high", "signalCoverage": { "recovery": { "usable": ["readiness"], "missing": ["sleep"] }, "training": { "usable": ["trainingLoad"], "missing": [] } }, "decisionBasis": { "governingRule": { "ruleId": "EVD-R-002", "measured": { "quantity": "readiness_score", "value": 48 } } } }
Pacevera does not fill missing values with defaults. signalCoverage.recovery describes current recovery-signal availability; signalCoverage.training describes whether recent workouts include the training-load data required for fatigue calculations.
| Deployment mode | Status | Boundary |
|---|---|---|
| Local desktop extension | Available | Runs through stdio on the user's computer. The Pacevera process does not fetch provider data, persist Evidence, or make model calls. |
| User-controlled private deployment | Planned | Intended to run in a device, private network, or VPC controlled by the user or organization. |
| Hosted remote deployment | Not available | The repository contains resource-server readiness code, but production deployment, authorization infrastructure, and hosted privacy controls are not complete. |
The desktop extension has no runtime dependencies beyond the Node.js standard library. It does not use analytics, telemetry, crash reporting, provider accounts, or provider OAuth tokens.
The desktop extension processes the minimum health-related Evidence supplied by the caller for the requested fitness decision. It does not retain, sell, use for model training, or use Evidence for unrelated purposes.
The extension makes no outbound network requests and sends Evidence nowhere. On the user's own computer it does keep durable records: a bounded continuity record, and a local SQLite store holding the decisions it produced, the outcomes the user reports back, and the derived state behind them. Both are the user's to export or delete. The AI host, operating system, imported files, and any host conversation history are outside the extension's control and are governed by their respective policies.
See PRIVACY.md for the complete policy and deployment scope, and TERMS.md for the terms of use. The canonical versions are published at https://pacevera.com/privacy and https://pacevera.com/terms.
Pacevera is not a medical device and does not provide medical advice. It is intended for general fitness and training purposes only.
Pacevera is distributed as a Claude Desktop extension (.mcpb).
pacevera.mcpb from Releases. shasum -a 256 pacevera.mcpb
The extension requires Node.js 20 or newer. Local persistence of decision traces and outcomes needs Node.js 22.5 or newer, which is where node:sqlite exists; on Node 20 or 21 the extension installs and runs without it, and reading your selected export folder for a decision is unaffected. The local plan decision is offered only once this machine holds a plan and its context, so a fresh installation does not list it — that depends on what is stored, not on the Node version.
Claude Desktop and other local MCP hosts are supported through the desktop extension, and Claude's own Dispatch can drive that installed extension from a phone with no remote deployment anywhere in the path — it needs the desktop app running, a Pro or Max plan, and the feature to be available to you. A Pacevera-operated hosted remote deployment is still not available for public use.
The current public release is v0.5.8, using Decision Engine 1.12.0 and base_rules@1.6.1. It includes ten public tools, bounded local continuity, personalized single-workout generation, decision traces, package validation/dry-run/rollback, and an optional local Google Health connection. The Oura and WHOOP readers were implemented from their published API specifications and have not yet been validated against real responses; Apple Health, Garmin, Google Health, and Strava readers were developed from real export files.
Pacevera is proprietary software. See LICENSE for the applicable terms.
The Claude Desktop extension includes Today’s Brief, evidence-first local export reading, and plain-language tool titles. During installation, choose Your exported health data folder and select the parent folder containing any of these optional subfolders:
Your exported health data folder/
├── export_apple_health/ # Apple Health export.xml ├── export_garmin/ # Garmin Export Your Data / DI_CONNECT ├── export_strava/ # Strava activities.csv └── export_google_health/ # raw/ for JSON you pulled yourself,
Pacevera reads the selected folder locally; missing sources are reported as unavailable rather than guessed. The MCPB checksum is published in the release notes.
v0.5.8 includes an optional Google Health connection that runs on your computer. You approve it in your own browser, or by scanning a QR code with a phone; the browser route reaches Google with no Pacevera server anywhere in its path, and the QR route passes through a Pacevera relay that handles only a short-lived authorization handoff — never your health data, your tokens, or the PKCE secret that completes the exchange on your machine. Whichever route you finish cancels the other.
In v0.5.8 the connection normalizes each Google Health response in memory and writes only the resulting evidence; the provider response itself is never written to disk. You can also disconnect from inside the app: it revokes the grant at Google, deletes the stored credential, deletes the evidence earlier syncs wrote, and clears the derived records from the local store. Files you placed in the folder yourself are reported back for you to delete, never removed for you.
This connection is capped at 100 accounts, and Google will warn you that it has not verified the app. Pacevera's Google app moved out of Testing into Production on 2026-08-20, so an invitation is no longer required — but Google's verification review for the health scopes is not complete. Until
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