"Python context management and dependency solving in ComfyUI" matching MCP servers:

Enables MCP clients to normalize messy FHIR R4 exports, reversibly de-identify them, compile compact citation-anchored clinical context, and verify model answers against the source record.

MyChart MCP Server

An MCP server for querying the KEGG bioinformatics database, providing tools, resource templates, and guided prompts for pathways, genes, compounds, and more.

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.

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.

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.

TransBench is a translational research agent that takes free-text clinical observations, decomposes them into biological axes, generates falsifiable hypotheses grounded in PubMed evidence, and designs reproducible computational experiments with concrete datasets for Claude Science.

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

Enables Claude Desktop to query and analyze diabetes data from Omnipod 5 and Glooko through natural language, providing clinical audit and triage insights such as time in range, trends, and bolus analysis.

Taiwan's first public Model Context Protocol server for National Health Insurance data — rejection codes, ICD-10 mappings, audit indicators, semantic wiki search. Powered by OPDSTAR.

Privacy layer for healthcare AI agents. Pseudonymises patient identifiers (NHS numbers, names, dates of birth, addresses; UK and US) into labelled tokens locally before text reaches an agent, then restores the originals afterwards, keeping the token map out of agent context.

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.

Renders interactive 2D molecular structure diagrams from SMILES notation and computes molecular properties like molecular weight, LogP, and TPSA, directly in the chat.

Search 200M+ patents and scientific literature in natural language using PatSnap's global R&D intelligence database.

Enables AI assistants to answer healthcare REIT portfolio questions with deterministic, provable answers grounded in Omega Healthcare 10-K filings and CMS nursing home data, including status, caveats, and provenance.

Provides phenotype-aware cardiovascular triage tools including FHIR R5 case retrieval, missing-data analysis, ECGFounder-backed ECG interpretation, risk summarization, and structured SBAR handoff in multiple languages.

Enables checking whether a medicine has a reported shortage in Portugal (Infarmed monitoring, export-suspension and prior-notification lists) and finding pharmacies in a municipality that are on duty today or open now, with addresses, phone numbers and distances. Also surfaces the relevant help lines and next steps, read-only from public sources and without pharmacy stock data.

Identifies plants from photos and determines whether a species is native, introduced, or invasive in a given country, drawing on GBIF, GRIIS, and GISD data, and also provides management recommendations and country alien-species lists.

Enables MCP clients to annotate and classify single human genetic variants in any notation, returning an auditable points-based ACMG verdict with its criteria, gnomAD frequencies, in-silico predictors, ClinVar data, and per-transcript consequences. It is read-only, requires no account or API key, and keeps answers compact while linking back to the source.

Enables editing and querying of Gene Ontology Causal Activity Models (GO-CAMs) through the Barista API. Supports model creation, individual and fact management, evidence addition, and causal pathway construction for biological knowledge representation.

A Model Context Protocol (MCP) server for searching the National Provider Identifier (NPI) registry. This server provides tools to search and retrieve information about healthcare providers and organizations in the United States.

Enables AI assistants to upload clinical documents and medical device images for health data extraction, normalization, and retrieval of structured coded results in formats such as JSON, FHIR, HL7, CSV, and Parquet.

Enables AI agents to read and analyze Dexcom CGM data through tools for current glucose, recent historical readings, and glucose statistics such as time in range.

Connects DHIS2 health information systems to AI assistants via the Model Context Protocol, enabling natural language queries for analytics, metadata, and tracker data.

Translates HL7 v2.x messages to FHIR R4, validates against profiles like US Core, and explains errors in natural language for AI agents.

A Model Context Protocol (MCP) server that gives AI assistants direct access to the World Health Organization's Global Health Observatory (GHO) for comparative health systems research.

Read-only FHIR chart tools for agents, with opt-in human-approved write proposals through MCP elicitation.