"Blender Scene Generation and Importing into Unreal Engine" matching MCP servers:

Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.

MCP server for tracking nutrition meals and workouts, integrating with claude.ai to manage food logs, macros, exercise catalogs, and generate daily/weekly summaries.

MyChart MCP Server

An MCP server that converts structured cycling workout specs into MyWhoosh .zwo and Garmin Connect workout files, with tools for validation, description, and rendering. It also includes skills for uploading workouts to both platforms.

MCP server that lets you ask questions about your Garmin training history in plain language. It ingests FIT files into DuckDB locally and exposes typed tools for analyzing activities, streams, and summaries.

A stateless MCP server that normalizes strength training logs into a deterministic canonical schema, enabling consumers to build analytics downstream without storing data server-side.

MCP server for the Google Health API: heart rate, activity, sleep, SpO2, HRV, ECG and irregular-rhythm notifications, read into a local SQLite cache for fast offline queries and trend analysis. OAuth 2.0 with automatic token refresh, incremental sync, a cache-only offline mode, and a doctor command that diagnoses a setup without spending quota.

Enables AI agents to analyze synthetic biomarker panels via Phi Longevity's PRISM clinical recommendation engine, providing tiered, guideline-cited recommendations. Also offers tools to list supported biomarkers and retrieve methodology.

Real-time human state awareness for AI agents. Fuses cardiovascular, vocal, visual, and textual signals into a unified stress score (0-100). Streamable HTTP transport with 4 tools: ingest_signal, get_human_state, get_history, delete_subject.

Query your Apple Health data including sleep, heart rate, steps, workouts, and more by ingesting an exported XML archive into a local SQLite database.

An MCP server that transforms Garmin data into compact, verdict-first coaching reports for LLMs, computing metrics like CTL/ATL/TSB and ACWR to answer training readiness questions.

Enables AI assistants to access and analyze Polar device health data, including exercises, heart rate, sleep, and recovery metrics, by preprocessing raw sensor data into compact summaries to avoid context window overload.

Brings Garmin training data into Claude via Intervals.icu, enabling querying of activities, wellness, and planned workouts, as well as creating structured workouts that sync back to the Garmin watch.

Aggregates and analyzes fitness data from multiple sources like Whoop and Strava through a modular adapter architecture. It enables users to monitor health metrics, track activities, and gain insights into sleep, recovery, and training performance.

Enables reserving, canceling, and listing fitness classes on AimHarder through natural language, with support for multiple boxes and waitlists.

Enables AI agents to sync WHOOP recovery, sleep, workouts, cycles, and body-measurement data into a local Postgres database and query it through fast, offline-capable MCP tools without repeatedly hitting WHOOP API rate limits.

Read/write MCP server for Intervals.icu — 51 tools spanning activities, streams, wellness, calendar, gear, and sport zones, plus structured workout generation with a built-in syntax reference for cycling, running, and swimming.

An MCP server that provides access to Cronometer nutrition data, enabling users to pull food logs, macro and micronutrient summaries, and biometric data into Claude or Cursor. It supports daily nutrition tracking and raw CSV exports by interfacing with the Cronometer web protocol.

An ingredient-based recommendation engine that identifies similar products using TF-IDF vectorization and scans ingredient lists for potential irritants. It enables users to perform NLP-based product matching and check for skin-sensitivity red flags within Claude.

Enables AI assistants to manage recipes, meal plans, and shopping lists in Mealie through natural language, supporting CRUD operations and URL-based recipe imports.