"A tool or platform for taking quick notes" 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.

Enables scoring the WHO-5 Well-Being Index from five answers, returning a 0–100 score and a low, reduced, or normal band without providing a diagnosis.

Exposes clinical question answering, guideline search, and minimum-necessary FHIR patient context as tools to any MCP client.

Manages blood pressure readings (create, read, update, delete) via an MCP server, integrable with Open WebUI.

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.

Enables LLM agents to query de-identified FHIR-shaped hospital data through audited, read-only tools for patients, encounters, conditions, observations, medications, and interaction checks, while any medication write stays a draft that a clinician must confirm out-of-band.

Integrates with Get Notes API to search and retrieve knowledge from configured knowledge bases with AI-powered synthesis and raw recall capabilities.

Enables genomic sequence analysis through the Evo 2 model, supporting DNA sequence scoring, embedding, generation, and variant effect prediction with multiple model checkpoints (7B, 40B, 1B parameters).

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

Enables variant annotation and effect prediction using the Ensembl VEP API, with support for batch and single queries.

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 Claude to read a user's Oura Ring data—including sleep, readiness, activity, stress, workouts, heart rate, and personal info—through a self-hosted, read-only connector deployed to the user's own Vercel account.

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.

An open source biomedical research agent that provides LLMs with 28 tools for drug discovery, protein analysis, literature search, medical imaging, omics, and sandbox execution, all running locally via Ollama and MedGemma.

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.

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.

Explains why two scientific papers disagree. A contradiction explorer for bench scientists that compares two studies' designs and grounds every claim in a verbatim quote from the source text.

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.

Verified ICD-10-CM code lookup & validation for AI agents — official descriptions, not guesses.

Enables AI assistants to clean PDB structures and run initial-stage energy relaxation for biomolecular modeling. It provides a structured workflow for preparing structures before production molecular dynamics or coarse-graining pipelines.

Monitors PubMed and medRxiv for configurable research topics, summarizes papers using a local LLM, and stores deduplicated results in a local database.

Enables querying Anvisa's open data for drug registration status and recent medical devices, with heuristic AI-use classification using a locally hosted LLM.

Enables AI agents to search a directory of Iranian doctors by full or partial name, city or province, and specialty, and returns the best match with alternatives plus clinic addresses, phones, weekly hours, and map links. It is read-only and requires no authentication, so it cannot book appointments or provide medical advice.

An MCP server for longevity and metabolic medicine that provides a medication catalog, dosing protocols, contraindication screening, drug interaction checks, lab recommendations, and patient intake pathways across 35 compounds.

Enables validation of clinical notes in SOAP format, checking required fields and semantic coherence using a local LLM, all processed locally with no data leaving the machine.

A Model Context Protocol (MCP) server for interacting with Gen3 data commons, with GraphQL query validation to reduce hallucinations.

Enables a dental office's AI agent to verify benefits for a batch of up to 25 patients in a single MCP call, returning coverage percentages, frequency limits, waiting periods and deductible/annual-maximum remaining, each tied to a plan-clause citation. Exceptions such as identity mismatches or ambiguous cases are routed to a human review queue rather than guessed, with every call audit-logged.

Enables agents to interact with a clinic booking API, including listing specialties, doctors, and a patient's appointments, and booking or cancelling appointments when the active profile permits, while preserving the caller's authority and screening tool descriptions for safety.

Enables LLM clients and agents to produce realistic synthetic medical referral letter PDFs — a German Überweisungsbrief/Arztbrief or the same letter in another language — either from structured JSON with deterministic, seeded rendering or from a free-text description written by a configured LLM. Each call returns the finished PDF as an embedded resource plus the completed letter content and its seed as structured data.