Skip to main content
Glama
91,527 servers. Updated

Matching MCP tools:

Matching MCP Connectors:

"A platform for locating illustration images for website design" matching MCP servers:

GET /v1/servers – MCP directory API reference
  • A
    license
    A
    quality
    B
    maintenance
    Enables AI agents like Claude Desktop, Cursor, and VS Code to connect directly to COLMI R02/R03 and compatible smart rings over local Bluetooth LE, exposing tools for ring scanning, battery and firmware status, activity and sleep/recovery insights, real-time heart rate and SpO2 vitals, 3-axis motion sampling, clock sync, and physical LED blinking. Runs fully locally with no vendor cloud, accounts, or subscriptions.
    8
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables Alexa+ users to coordinate household pet care by logging feeding, medication, activity, litter, and health observations for dogs and cats, with evidence-grounded triage, Q&A, and daily briefings backed by a verified veterinary library and citations.
    3
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    A daily-rhythm support MCP server for ADHD and bipolar disorder, providing 23 tools for mood tracking, social rhythm regularity, early warning detection, task breakdown, and crisis support, all running locally with zero dependencies.
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    Integrates healthcare data from multiple sources (HL7 v2, FHIR, DICOM, device telemetry) and provides clinicians with secure, role-based access to patient context, care unit summaries, device events, diagnostic exams, and other clinical data through specialized MCP tools.
    MIT
  • F
    license
    Not graded
    quality
    Not graded
    maintenance
    Connects AI assistants to fitness data from over 150 wearables including Strava, Garmin, and Fitbit through the Model Context Protocol. It provides 47 tools for sports science-based analysis, training load management, recovery tracking, and personalized nutrition planning.
    16
    -
  • F
    license
    Not graded
    quality
    B
    maintenance
    Exposes Garmin Connect health and activity data (steps, sleep, heart rate, etc.) via MCP tools, with built-in login and MFA support.
    -
  • A
    license
    A
    quality
    B
    maintenance
    An MCP server that provides a USDA-accurate food database with deterministic macro math, enabling tools like list_foods, get_food, calculate_macros, filter_by_diet, build_meal, and list_available_tags. It allows Claude to look up nutrition facts and solve for exact macro targets offline, without AI or network.
    6
    MIT
  • A
    license
    A
    quality
    A
    maintenance
    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.
    6
    19
    67 PyPI
    GPL 3.0
  • A
    license
    A
    quality
    B
    maintenance
    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.
    6
    MIT
  • A
    license
    A
    quality
    A
    maintenance
    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.
    10
    17 npm
    1
    MIT
  • A
    license
    A
    quality
    A
    maintenance
    SuperGlookoQuery is a Claude Desktop extension (MCPB) that connects to Glooko diabetes device data and exposes it as clinical analysis tools (time in range, GMI, trends, enriched bolus/basal analysis, charting), for any pump/CGM combination Glooko supports rather than one fixed device. It's a fork of Richard Hall's podquery-mcp, reworked to discover each account's own data shape rather than assumi
    2
    16
    MIT