"Using agents in VSCode to reference library documentation during programming" matching MCP servers:

Enables users to describe workouts in plain English and have them created as structured Garmin Connect workouts with pace, HR, power, cadence targets, and repeat blocks. Also provides full workout lifecycle management including listing, updating, deleting, and scheduling to the calendar.

Provides local MCP tools to query your own Xiaomi Mi Fitness health data (sleep, workouts, heart rate, etc.) stored in a local SQLite database, enabling AI assistants to access personal health records without exposing credentials.

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.

Ask your Oura Ring about sleep, readiness, activity, stress and heart rate in ChatGPT or Claude, in any language. Read-only, 10 task-oriented tools; runs in a sandbox demo mode with no credentials.

An MCP server that lets Claude plan cycling training in intervals.icu, upload workouts to the calendar, and review planned versus actual outcomes, fitness trends, and power curves.

Provides Claude Code and Claude Desktop with safe, read-only access to your local Garmin training data, readiness decisions, run details, and trends so you can get coaching advice in natural language.

Enables AI agents to read and analyze your Boardsesh climbing logbook across boards like Kilter, Tension, and MoonBoard, with read-only access and optional credentials for personalized recommendations.

Enables AI agents to read and analyze your Kilter Board logbook, including sessions, sends, projects, and grade progress, entirely read-only.

MCP server for Cronometer nutrition tracking using the mobile API. Enables food logging, nutrition data retrieval, diary management, and fasting tracking.

This MCP server enables logging workouts in plain language through AI assistants and provides tracking of sessions, programs, records, estimated 1RM, and per-muscle load, with coaching informed by the user's logged data.

MCP server for Bosch eBike Flow (Smart System / BES3). Read-only access to battery health and charge-cycle trends, components and firmware, live state-of-charge, and per-ride activity data (distance, elevation, power, assist-mode, CO2), signing in with your own Bosch account via PKCE.

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.

Enables MCP-capable AI agents to read Zepp/Amazfit data, including workouts with GPS/HR/power tracks, splits, daily activity, sleep, readiness, HRV, PAI, stress, SpO2, and devices.

MCP server to read daily activity, sleep, heart rate, and body metrics from Google Health API, allowing AI assistants like Claude to access your health data. Optionally syncs health metrics to an Obsidian vault.

Enables agents to read Mi Band health records from a computer, providing recent status, daily reports, historical details, and data sync via Gadgetbridge and USB, with agent-guided setup.

Provides a unified MCP interface to a personal health database, enabling AI agents to sync lifting workouts from Hevy, log food intake against a catalog, and run read-only SQL queries to cross-reference training and nutrition data.

Connects AI assistants to SmartGym on Mac, enabling users to review workouts, tweak routines, and build training programs in plain English, with changes syncing to iPhone and Apple Watch.

Enables AI agents to securely read and analyze your Google Health data from Fitbit, Pixel Watch, and Health Connect, providing baseline-aware insights, readiness scores, trends, and anomalies while keeping data local and read-only.

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.

Enables AI assistants to read your SisRUN training plan with your own credentials and answer questions about prescribed workouts, like weekly coach plans, in a structured format.