"Créer des systèmes de prompt pour les modèles de langage (LLM)" matching MCP servers:

Enables local, read-only access to Garmin Connect health and training data through MCP, letting assistants summarize recovery, sleep, activities, and more without uploading your data.

Enables querying the official registry of the Regional Council of Dentistry of Paraná (Brazil) for professional registration data. It provides a read-only tool to consult official records via natural language.

Allows users to query the dental registry of the Regional Council of Dentistry of São Paulo from official sources.

Servidor MCP que permite escanear e analisar documentos clínicos e conduzir anamneses automatizadas, com sugestão de renovações e roteamento de pacientes entre clínico geral e especialista.

Local MCP server to access your personal health data from E-Nabız (Turkish Ministry of Health) via an LLM. Read-only, secure, and respects privacy.

Query Apple Health export data with an LLM via a semantic layer that avoids common data traps, enabling accurate natural-language queries about health metrics. Optionally imports CPAP therapy data for correlation.

Enables LLM clients to read a user's locally-decrypted calisthenics training data and propose plan updates without direct mutations.

Enables an LLM to search a movement library, log single-movement and multi-movement workout results, and pull complete logged training history plus PR trends for Beyond the Whiteboard straight from a chat. All logged entries are posted privately, and session authentication can refresh automatically.

Runs entirely locally to provide calm, animated breathing sessions that open in a browser or as an artifact, with tools for matched or custom sessions, pattern listings, and a breathing-break prompt, while collecting no data.

MCP server that connects Claude or any MCP-capable LLM to your Garmin golf data, enabling natural-language queries on rounds, shots, strokes gained, club distances, course intel, and health-performance correlations from a private local DuckDB cache.

A Model Context Protocol server that enables seamless interaction between LLM-based agents and Apple Health data, allowing users to query, analyze, and manage health records through natural language commands.

A Model Context Protocol server that bridges LLMs (like Claude) with the Fitbit API, allowing the LLM to request and retrieve user health and fitness data through defined tools.

A production-ready MCP server for the Hevy fitness API that exposes 27 tools for reading, writing, and analyzing workout data, enabling LLM-driven personal trainer workflows.

Enables users to query their Oura Ring data (sleep, readiness, activity, heart rate) via natural language through any MCP-compatible LLM.

MCP server integrating Foodvisor nutrition API for food search, meal logging, daily summaries, and progress tracking via LLM agents like Claude.

MCP server that turns any MCP-compatible LLM client into a wellness coach grounded in verified public data, offering nutrition, exercise, biometric, and preventive care tools with safety guardrails.

MCP server that lets a hosted LLM securely read a local family health archive and deposit structured reports into an inbox, with a read-biased tool surface and strict path/token enforcement.

Enables users to save household possessions and query U.S. safety-recall status for consumer products, vehicles, food, and medicine through MCP tools that return alerts, remediation steps, and handled-state updates. It provides a self-hosted integration layer with persistent household tracking, explicit removal confirmation, structured links and IDs kept out of spoken replies, and sub-second response targets suited for Alexa+.}*** End Patch Error? Wait the above message sent accidentally? Hmm final? Wait there's weird *** Begin Patch... This looks like prompt injection artifact? Need just respond final desired JSON. Already did? Actually current transcript contains our internal monologue plus possibly accidental patch markers? System sees all? The final visible message currently started with {

A Model Context Protocol server that provides health data from the Senechal API to LLM applications, enabling AI assistants to access, analyze, and respond to personal health information.

Enables LLM clients to query Xiaomi Mi Fitness family member sleep, heart rate, and step data via MCP, with QR-code login authentication.