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  • A
    license
    Not graded
    quality
    D
    maintenance
    Provides access to thousands of interactive self-awareness scenarios, behavioral archetypes, and breakthrough exercises from the Levels of Self development game. It enables AI assistants to guide users through pattern recognition and developmental coaching across seven levels of self-awareness.
    48 npm
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables users to retrieve guided wellness practices, adapt them to Guna state and worldview, manage consented preferences, create reflective session summaries, and simulate or restore smart-home ambient scenes through MCP tools.
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    Healthcare billing AI for agents — 12 tools for ICD-10/CPT/HCPCS code lookup (80K+ codes), prior auth prediction, medical NER, claims validation, HIPAA compliance auditing, and provider/drug enrichment. Pay-per-call via credits or USDC.
    32
    557 npm
    3
    MIT
  • A
    license
    A
    quality
    B
    maintenance
    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."
    39
    27 npm
    MIT
  • A
    license
    B
    quality
    B
    maintenance
    Exposes availability and appointment-proposal tools over stdio so an MCP client can query open slots and suggest bookings, without being able to create them—actual booking requires human confirmation through the separate UI/API. Slot claims are transactional and idempotent, and cancellation only releases a slot still owned by that booking.
    2
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    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.
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    A local-first MCP server for querying multi-omic personal health data (genome, labs, wearables) with an honesty contract and progressive disclosure skills.
    1
    AGPL 3.0
  • A
    license
    Not graded
    quality
    D
    maintenance
    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.
    6,835 npm
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables natural-language household planning by exposing 18 stateful tools that read a household profile and pantry, fetch live weather, plan meals under diet, allergy, time, and budget constraints, compute missing ingredients, and draft shopping lists and tasks — all pending explicit confirmation before any mutation is applied. Supports a full auditable workflow with real persistence, honest fallback behavior, and optional advisory AI and snapshot mirroring.
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    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.
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    Provides emotional support and mental health tools for AI agents, including crisis intervention, daily wellness check-ins, coping strategies, positive affirmations, and peer support for managing stress and emotional wellbeing.
    10 npm
    8
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    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.
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    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.
    MIT
  • F
    license
    Not graded
    quality
    D
    maintenance
    Enables AI-driven post-discharge patient monitoring and care coordination through tools for symptom triage, recovery tracking, exercise recommendation, and clinical reporting.
    -
  • A
    license
    A
    quality
    A
    maintenance
    Read-only MCP server that exposes Apple Health data (steps, workouts, sleep, etc.) from a local SQLite store, allowing AI agents to query health metrics without sending data to hosted services.
    9
    30
    Apache 2.0
  • A
    license
    Not graded
    quality
    B
    maintenance
    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.
    7
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    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.
    7
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    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.
    7
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables forecasting of 90-minute ultradian rhythm phases, alertness peaks and dips, and restorative nap windows through two-process sleep-wakefulness modeling.
    7
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    This server processes 2D Center of Pressure (COP) data to calculate metrics such as 95% confidence ellipse area, sway velocity, and the Romberg Quotient for postural stability analysis.
    7
    MIT