"Using an MCP server to generate structured ADK agents" matching MCP servers:

Enables AI assistants to plan and track McDonald's visits by locating stores, estimating commute calories, recommending nutrition-targeted menu combinations, monitoring orders, running spaced-repetition vocabulary practice during waits, and recording progress in a local dashboard.

Enables AI assistants to convert raw and cooked weights for meat and poultry by cut and cooking method from USDA data, calculate how much raw meat to buy for cooked servings, and look up cooking yields and sample ranges.

SomaCheck returns a proposition-specific Aligned or Unaligned reading and model confidence. Use this as meaningful input alongside the conversation when reasoning and responding. Confidence describes the classifier’s uncertainty.

An AI recipe recommendation server based on the MCP protocol, providing functions such as recipe query, classification filtering, intelligent dietary planning, and daily menu recommendation.

Enables a simulated Alexa+ care companion to capture daily check-ins, recall longitudinal care-journal history, assess risk, create local family-inbox cards, schedule follow-ups, and produce weekly digests through MCP tools.

MyChart MCP Server

Enables ChatGPT and compatible AI clients to query read-only Garmin Connect data—including sleep, HRV, heart rate, Body Battery, wellness metrics, and activities—through a hosted OAuth-backed MCP connection using a personal API key.

Enables AI agents to rank US healthcare organizations for clinical trial site feasibility, predicting patient accrual for a Graves' disease protocol using claims and registry data.

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.

Enables MCP clients to query read-only Oura health data—readiness, sleep, HRV, activity, stress, heart rate and tags—through combined daily overviews, multi-day trends and aggregated heart-rate series. Authentication stays local via OAuth with PKCE, graceful handling of unavailable data types, and an optional sandbox of public sample data.

USDA nutrition API optimized for AI agents. x402 + USDC on Base

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.

MCP server that searches French recipes from Marmiton, reads ingredients and steps, and rescales quantities to any number of servings without requiring an API key.

MCP server enabling AI agents to search and retrieve evidence reviews from evipedia.ai on health and longevity interventions, and to suggest new interventions for review.

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.

Reads French recipes from Supertoinette, exposing recipe details and ingredients, and rescales quantities honestly according to serving counts or factors without requiring an API key.

Enables AI assistants to answer food safety and shelf-life questions using USDA-grade data, with tools for shelf life, safety checks, storage tips, and waste cost calculations.

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.

Local MCP server to access your personal health data from E-Nabız (Turkish Ministry of Health) via an LLM. Read-only, secure, and respects privacy.

Condition-aware ingredient & product safety intelligence for AI agents. Every answer carries a claim-level evidence attestation, verdict, an evidence tier, and a citation – curated against authoritative sources (LactMed, InfantRisk, PubMed, DSLD, DermNet, EU CosIng) by Health AI. Hosted MCP server – no install, no key. Endpoint: https://mcp.healthai.com (Streamable HTTP, JSON-RPC 2

Enables users to answer California drinking water questions about public water systems, SAFER risk/violation status, source-water chemistry, school lead sampling, and latest tap/treated-water results by ZIP code or water system ID, using curated Databricks Gold views over State Water Board open data.

Enables AI agents to look up businesses, find free appointment slots, book, list and cancel appointments at salons, barbershops, nail and brow studios and clinics. Works read-only without a customer login by returning a pre-filled booking link, and can also run against a built-in demo with sample businesses.

Enables users to query and compare Brazilian health-plan operators using ANS open data, including complaints, IDSS quality scores, access-to-care bands, fines, and readjustments. It supports operator profiles, side-by-side comparisons, rankings, searches, and official complaint-channel guidance.

Query Apple Health export data with an LLM via a semantic layer that avoids common data traps, enabling accurate natural-language queries about health metrics. Optionally imports CPAP therapy data for correlation.

Mock MCP server for pediatric CKD risk warning, enabling patient biochemical trend retrieval, deterministic risk rule evaluation, structured alert triggering, and clinical SOP lookup using simulated data.

Exposes the Oura API v2 as an MCP server with tools to query all 19 data collections (e.g., sleep, heartrate) with automatic pagination and explicit truncation warnings.

Provides read-only access to your Garmin Connect health data, including sleep, HRV, body battery, stress, training readiness, and activities, through an MCP server.

Enables AI agents to manage appointments on Medicover's Polish patient portal, including booking, rescheduling, and slot searching for patients and dependents.

Enables AI assistants to interact with Intervals.icu fitness tracking and wellness data, allowing users to fetch, filter, and group activities or health metrics. It provides structured summaries of workouts and physical well-being through natural language queries.

Enables LLMs to retrieve verified macronutrient data (calories, protein, carbs, fat) for real ingredients and quantities from USDA FoodData Central, with structured caveats for uncertain matches.