"How to allow an LLM to ask questions to a user" matching MCP servers:

Enables natural-language querying of a mock legacy healthcare database and returns validated FHIR resources (Patient, Observation, Condition).

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.

Enables AI assistants to read COVID-19 lateral flow test results from photographs by calling a deployed computer-vision pipeline, returning verdicts like positive or negative with confidence.

Provides tools for managing pharmacy accounts, user information, and campaigns via a local MCP server that interfaces with the EDB API.

MyChart MCP Server

An MCP server that enables LLMs to securely query synthetic clinical data through validated, scoped tools (patient summaries, conditions, medications, lab trends, encounters) while maintaining audit logs and access controls.

Enables a connected LLM to inspect brain MRI slices as crops and montages with coordinates, compare a region against its mirrored hemisphere, and review the pipeline's candidate hotspots. It lets the model write prioritised "area to review" annotations that appear live in the browser viewer, and move or read the clinician's crosshair position.

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.

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).

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

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.

Enables clinical question answering via OpenEvidence with citation verification, including tools to ask questions, retrieve results, and follow up, plus an integrated skill to check citations against primary sources.

Enables natural language querying of healthcare claims data by exposing a SQLite database with read-only SQL tools, allowing users to ask questions in plain English and get answers backed by real database queries.

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.

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 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.

Enables querying Brazilian PCDT clinical protocols from Conitec and generating concise, context-specific treatment summaries using a local LLM, with verified literal citations and links to official PDFs.

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.

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.