"Setting up SQL Server connections for agent querying" matching MCP servers:

Read-only MCP server for accessing glucose readings, charts, logbook, and statistics from LibreLink Up sensors, supporting any MCP client.

Family meal planning run by your own AI agent: it proposes ten dinners each week, the household votes and leaves feedback from personal links, the top picks win, and a grocery list is built minus what's already in the pantry. Remote MCP server at https://agentchef.net/mcp; connect with an API key and say "Run Agent Chef."

Exposes wellness data such as sleep, activity, heart rate, and stress as MCP tools so AI agents can retrieve current vitals, pull historical records, and analyze trends. Supports simulated physiology along with Fitbit and planned Apple Health providers.

A local-first MCP server for querying multi-omic personal health data (genome, labs, wearables) with an honesty contract and progressive disclosure skills.

A universal fitness intelligence layer for AI assistants like Claude, ChatGPT, and Copilot, enabling user profiles, workout/diet plans, calendar scheduling, and gamification via MCP and REST APIs.

Gives Claude read-only access to your own ring's health data — sleep, readiness, HRV, heart rate, activity, workouts, stress, resilience, SpO2, VO2 max and cardiovascular age — from claude.ai, desktop, and mobile. Runs as a private remote server on your own Cloudflare Worker, locked to a single account with OAuth-encrypted tokens and no stored health data.

Enables clinical teams to list patients with active sharing and read glucose, graph, logbook, and statistics from LibreLink Up, with secure magic-link login and encrypted credentials.

Enables turning any personal-assistant REST backend into Claude-ready tools via a single MCP server, providing 38 tools for communications, finance, health, and more.

Enables circadian-aware scheduling of cognitive work, ambient flow-state detection, and utility-gated interruption decisions so proactive personal-agent interventions respect focus and urgency.

Your AI running coach that actually remembers. An MCP server with persistent memory that connects your Strava data to Claude — tracking your zones, pace trends, injuries, and goals across sessions so coaching advice stays current.

Enables a personal agent to read selected live Garmin Connect activity, readiness and device fields and, only after explicit approval of an exact preview, to create, schedule and request device synchronization of one fixed 20-minute running connectivity test over stdio. Login credentials never enter the model-facing tool surface, and no other workouts can be created, edited or deleted.

Enables Claude and other MCP apps to query the user's own activity and health data—sleep, HRV, Body Battery, stress, heart rate, steps, and workouts—locally and read-only.

MCP server for headless care coordination, providing tools for case-aware provider search powered by ai-carematch.

Provides local, Keychain-secured access to all 26 Garmin Connect Personal API GET endpoints plus 8 summary tools. Enables users to query sleep, HRV, Body Battery, activities, profile, weight, and other connected health data through their own Personal API key.

Exposes MCP tools that compute longevity and metabolic metrics (autophagy index, GKI, MAGE), cardio-renal biomarkers (BUN/creatinine ratio, cardiac output and TPR, nocturnal BP dipping), chronobiology estimates (DLMO, melanopic lux, caffeine clearance), plus neuro-recovery and biomechanics scores. Runs as a zero-dependency Python JSON-RPC 2.0 stdio server so any MCP-compatible client can query these physiological domain calculators.

A zero-dependency MCP suite exposing computational tools across metabolic, cardio-renal, chronobiology, neuro-recovery, and biomechanics domains. It enables clients to derive longevity and physiology metrics such as autophagy index, glucose-ketone ratio, glycemic variability, peripheral resistance, nocturnal BP dipping, DLMO clock time, melanopic lux, caffeine clearance, EEG fatigue entropy, and grip vitality age from user-supplied measurements.

Enables estimating sweat rate and sodium loss, modeling subclinical dehydration cognitive deficits, and generating personalized hourly fluid and electrolyte replenishment schedules.

Enables computing composite glycemic load for multi-ingredient meals, modeling protein and fat attenuation of glucose spikes, and forecasting post-prandial fatigue and stable focus hours to guide meal and task scheduling.

Enables users to model Lally habit automaticity curves, estimate behavioral friction price elasticity, and derive minimum viable micro-habits that protect streaks on low-energy days.

Enables modeling supplement pharmacokinetics, tracking elimination half-life and washout, evaluating competitive absorption conflicts, and generating optimized ingestion schedules.

Enables modeling ciliary eye-muscle fatigue and suppressed blink rates, estimating tear-film break-up, scheduling 20-20-20 optical recovery breaks, and calculating Hansraj cervical-spine torque for ergonomic posture remediation.

Enables users to model cumulative sleep deficits, estimate cognitive impairment using Van Dongen PVT kinetics, audit social jetlag, and generate circadian-safe gradual sleep repayment schedules.

Enables users to model two-compartment caffeine elimination, estimate adenosine A1/A2A receptor occupancy and slow-wave sleep suppression, and schedule intake windows and cutoffs from wake and bedtime.

Enables modeling of ocular light exposure, forecasting melatonin suppression delays from digital screens, and generating timed digital-sunset schedules for sleep readiness.

This MCP server enables users to model ocular light exposure and circadian melatonin onset, forecast screen-induced DLMO delays, and generate timed digital sunset schedules for light hygiene and sleep readiness.

Enables users to estimate VO2max from heart-rate ratios or Cooper 12-minute run distances, benchmark results against ACSM age and sex medians, and derive cardiorespiratory fitness biological age and all-cause mortality hazard ratios.

Enables users to forecast when habits become automatic, quantify how friction changes completion rates, and adapt routines into minimum viable micro-habits during low-energy days.

Connects WHOOP fitness data to Poke AI assistant, enabling natural language queries for recovery scores, sleep analysis, strain tracking, and healthspan metrics.

Enables organizing personal contacts into concentric social layers, estimating warmth decay via an exponential half-life model, and scheduling mindful reconnection touchpoints within a weekly cognitive bandwidth.

Enables Claude to access and analyze your Strava activities through OAuth authentication. Supports retrieving activity lists and detailed workout data for fitness tracking and analysis.