"An e-commerce platform for online stores and retail point-of-sale systems" matching MCP servers:

Enables AI assistants to interact with the Open Targets Platform API to search and retrieve comprehensive data about target-disease associations, drugs, genes, and drug discovery information through GraphQL queries.

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.

Enables quantum systems analysis and simulation including quantum circuits, open quantum systems, quantum chemistry calculations, many-body physics, quantum machine learning, and quantum field theory computations.

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 scenario-based clinical communication practice through MCP tools for discovering scenarios, starting sessions, sending practitioner turns, and receiving evidence-linked evaluation feedback.

MyChart MCP Server

Exposes four CMS public datasets as callable tools in Claude conversations, enabling natural-language real-world evidence analytics without SQL expertise.

A learning MCP server providing synthetic FHIR patient data with read tools and a gated write workflow (propose → human approve → commit) with structured audit logging.

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.

Provides secure access to VA's VistA electronic health record system, enabling AI applications to retrieve and summarize patient medical records for clinical staff.

This server enables interacting with the National Digital Health Mission's Health Information User (HIU) API, allowing agents to access and manage health information through the Multi-Agent Conversation Protocol.

An MCP server that gives LLMs live access to clinical trials, FDA drug recalls, adverse-event reports, drug labels, and drug-name normalization via six validated tools.

An MCP server that grounds protein research in the UniProt SPARQL endpoint, providing tools for querying proteins, sequences, variants, diseases, and more via intent-named tools and raw SPARQL.

An MCP server that lets an LLM answer a pharmacist's question about drug shortages by normalizing drug names, finding pharmacologic alternatives, and checking their shortage status using public FDA and NLM data.

Enables MCP-compatible clients to act as an AI receptionist for a small medical clinic, handling appointment booking and rescheduling, patient registration, intake, reminders, and FAQ answers.

Enables semantic retrieval and assembly of ICD-10-CM value sets from natural language descriptions for clinical cohort definitions.

Connects Claude to the U.S. National Library of Medicine MeSH APIs to search and retrieve medical authority data, descriptors, and qualifiers. It enables library and metadata staff to perform subject analysis and confirm terminology within an AI-assisted cataloging workflow.

Enables language models to search biomedical literature, fetch sequences, and follow links across Entrez databases through eleven read-only tools wrapping the nine NCBI Entrez E-utilities. It handles URL building, pacing, redirects, response caps, and API-key redaction so queries can be answered without a browser or scraping.

Grounds gene-nomenclature work in the HUGO Gene Nomenclature Committee (HGNC) dataset, enabling resolution of gene symbols and IDs to canonical HGNC identifiers, plus cross-references and batch operations.

An MCP server implementing the ROBINS-I V2 framework for risk-of-bias assessment in non-randomized studies, with deterministic algorithms and full provenance. It enables users to parse study documents, specify target trial results, answer signalling questions with evidence-bound quotes, and compute or override domain judgements.