"A server for reasoning about code using MCP" matching MCP servers:

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 comprehensive Model Context Protocol (MCP) server for accessing Human Protein Atlas data, providing information about protein expression, subcellular localization, pathology, and more.

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.

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

A specialized MCP server for Claude Desktop that enhances AI-assisted medical learning by fetching and processing educational resources from PubMed, NCBI Bookshelf, and user-provided documents.

Enables AI assistants to generate, validate, and optimize PLUMED input files for molecular dynamics simulations using a set of MCP tools.

Exposes vaccination-appointment scheduling as standardized MCP tools backed by an in-memory mock backend. Enables agents to list available slots by date and vaccine type, book appointments, check confirmation status, and cancel bookings.

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 searching the NIAID Data Ecosystem for biomedical research resources including datasets, clinical studies, and publications using Elasticsearch queries.

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.

Clinical research MCP server providing real-time access to PubMed (35M+ papers) and ClinicalTrials.gov (400K+ trials). Built for trial coordinators and life sciences teams. No API key required.

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.

Empowers AI agents with direct access to the official ClinicalTrials.gov database, enabling programmatic searching, retrieval, and analysis of clinical study data through a Model Context Protocol interface.

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.

Provides structured PubMed literature data for LLM agents, supporting search, caching, and open-access full-text downloads via the MCP protocol.

Enables AI agents to analyze synthetic biomarker panels via Phi Longevity's PRISM clinical recommendation engine, providing tiered, guideline-cited recommendations. Also offers tools to list supported biomarkers and retrieve methodology.

Exposes a clinic's knowledge base and structured records to Claude Desktop as callable tools, with read tools grounded with citations and write tools gated behind approval.

Enables querying a synthetic patient dataset with tools to look up patients by ID, age, disease, name, and get statistics, connecting Claude Desktop to local data.