"PostHog: Open-source product analytics platform" matching MCP servers:

CC0 open-data registry of community support helplines worldwide. TypeScript MCP server providing verified contacts with citation, staleness, and country-context guardrails. 15+ countries indexed.

Enables AI assistants to access the Open Food Facts database to query detailed food product information, nutritional data, and environmental scores. Supports product lookup by barcode, smart search with filtering, nutritional analysis, product comparison, and dietary recommendations to help users make informed food choices.

Enables Claude to ingest a local Samsung Health export into DuckDB and query monthly trends, period comparisons, trips, sleep timing, activity profiles, workouts, and custom read-only SQL while keeping raw data on the user's machine. It also generates a dashboard artifact with actionable next steps based on the user's aggregates.

Enables AI agents to query gym analytics—class attendance, trainer performance, and revenue insights—from existing CCTV camera feeds without new hardware.

Enables AI assistants to access food product information, providing nutritional analysis, product comparisons, and recipe suggestions using the Open Food Facts database.

Enables MCP clients to look up products by barcode, search products and text, retrieve taxonomy suggestions, and compare nutrition data through read-only tools.

Enables AI assistants to access food product information from Open Food Facts, including nutritional analysis, product comparisons, recipe suggestions, and allergen checks.

Enables users to access curated official Korean pregnancy and childbirth sources and find hospitals using HIRA directory facts.

Enables AI-driven pharmacogenomic analysis by querying structured genetic variant, drug response, and disease risk data. Supports natural language questions about medications, traits, and health risks based on user genome data, with privacy-first local execution.

Enables AI assistants to create, validate, and track personalized, location-aware exercise and eating routines using local profiles and open data, with privacy and safety guardrails.

Enables users to interact with their Strava data through natural language to analyze workouts, track fitness progress, and explore routes. It supports retrieving detailed activity stats, heart rate data, and segment insights directly within AI assistants.

Enables MCP-compatible clients to discover and use The Holistic Care's approved public mindfulness resources, including interactive games, guided audio practices, research summaries, a glossary, and the public PanchaVikas framework, through read-only tools and static resources. No authentication is required, and it wraps a public REST API without creating, modifying, or deleting anything.

Enables AI agents to resolve Japanese food names to nutrition facts per 100g based on official Japanese food composition data.

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.

Enables AI assistants and native clients to manage training plans, workout history, reusable recipes, meal records, and media through validated, versioned MCP and REST operations. It stores and validates structured fitness and nutrition data, including nutrition calculation, food catalog lookup, and Apple Health export status.

Provides Claude with SQL access to Hevy workout history and personal training conventions stored in a SQLite database. It enables detailed analysis of exercise progress, volume trends, and muscle group mappings through natural language queries.

Enables deterministic audiological evaluation of cochlear outer hair cell function, clinical pass criteria, and early noise-overexposure indicators through JSON-RPC tools for LLM and autonomous agent workflows.

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.

Enables LLMs to search for food products and retrieve detailed nutritional information from the Open Food Facts database using product names or barcodes.

Enables users to organise messy symptom notes into a clearer, portable appointment-preparation record through privacy-conscious tools for ChatGPT and Codex. It processes submitted text in memory without intentionally persisting it, supporting symptom diary capture and appointment-prep workflows.

Enables AI assistants like Claude to log and delete period and ovulation records, review cycle history and averages, and check the current cycle phase with predictions of the next period and ovulation window. Records are kept in the user's own Supabase instance behind key or OAuth authentication.

Enables querying Portugal's official SNS open-data statistics — hospital and health-unit locations, emergency visits by triage colour, surgical and consultation waiting lists, and all 149 Transparency portal datasets — from any MCP client. Read-only and keyless, it returns monthly national, regional or per-institution figures and can run custom ODSQL queries for anything the curated tools miss.

Official MCP server for Safe Mind, the German platform for the legally required psychological risk assessment (Gefährdungsbeurteilung psychischer Belastung). 12 tools: account onboarding, departments and locations, survey drafts, and anonymity-protected aggregated analytics that never return groups below the minimum size.

Privacy-first MCP server for querying personal health and finance data with AI. Built with Python, FastMCP, and SQLite. Local-first and open source.

Enables AI assistants to read Technogym mywellness training history, including workout sessions, per-exercise set data, per-second exercise analytics, and heart-rate traces.

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 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.

A stateless MCP server that normalizes strength training logs into a deterministic canonical schema, enabling consumers to build analytics downstream without storing data server-side.

Real US & Canada dental price data for AI assistants: average costs by procedure, state and city, insurance acceptance, and cheapest-state lookups — backed by open datasets (CC BY 4.0, permanent DOIs).