"Creating an MCP (Master Control Program) with any API" matching MCP servers:

Enables AI agents to query Human Phenotype Ontology clinical phenotype terms, navigate term hierarchies, and retrieve gene-disease and disease-phenotype annotations through keyless MCP tools.

Enables interaction with a comprehensive healthcare management system through FastAPI, supporting operations for patients, doctors, appointments, medical records, telemedicine, lab orders, prescriptions, insurance claims, and more with JWT authentication.

Provides oncology data (research, news, FDA approvals, clinical trials) and IBM MAMMAL biomedical predictions (PPI, DTI, ClinTox) as MCP tools. Allows AI agents to query cancer datasets and run predictions through a remote MCP server.

An MCP Server that provides access to Google Cloud Life Sciences API, enabling users to run biomedical workloads in the cloud through natural language interactions.

An MCP server that enables interaction with Google's Cloud Healthcare API, allowing users to manage healthcare data, FHIR resources, DICOM stores, and healthcare datasets through natural language commands.

Enables interaction with FHIR resources on Google Cloud Healthcare API through a SmartOnFHIR gateway secured by Firebase Auth, providing access to patient data, medical records, and medical research tools like PubMed.

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

A Multi-Agent Conversation Protocol Server that provides a natural language interface to the U.S. Department of Health & Human Services (HHS) Media Services API, allowing users to access health-related data and media resources through conversational AI.

Provides access to the Allen Institute for Brain Science API, enabling queries of datasets such as Cell Types, Mouse Connectivity, Atlases, and more via RMA queries and high-level tools.

Enables AI agents to query free biomedical and pharmaceutical APIs for clinical trials, drug data, molecular structures, adverse events, and research literature.

Enables interaction with the Atlas of Living Australia API to search and access 152+ million biodiversity records. Supports occurrence searches, spatial queries, bulk data downloads, and taxonomic data retrieval through natural language.

Enables users to query ClinicalTrials.gov using natural language instead of complex API parameters, translating plain English requests into structured API calls and returning organized clinical trial data.

Exposes DICOM operations as tools for AI agents to interact with medical imaging systems and PACS. It enables searching for studies and series, querying instance metadata, and retrieving pixel data from DICOM entities.

Exposes tools from the Ecuro Light API for managing clinical appointments, patient records, and clinic availability. It enables users to perform healthcare management tasks such as scheduling, patient search, and report generation through MCP-compatible clients.

Enables access to mock Epic patient data through 15 MCP tools with two-tier access (list summaries, then fetch details) and LLM-powered natural language search across allergies, medications, conditions, clinical notes, labs, vitals, and procedures.

An MCP server that provides access to Monarch Initiative's biomedical data through the Biolink API, enabling agents to query biological entities, associations, and knowledge graphs using natural language.

MyChart MCP Server

Provides access to an AI medical chatbot API for healthcare assistance, enabling natural language interactions such as neurosurgery queries.

Enables AI assistants to perform quality control analysis on high-throughput sequencing data using FastQC and MultiQC. It supports single-file and batch processing of FASTQ/FASTA files and generates comprehensive, interactive summary reports.

An MCP server that enables AI assistants to generate, score, and analyze DNA sequences using the evo2 genomic foundation model. It supports multiple execution modes including local GPU, SLURM clusters, and the Nvidia NIM cloud API for tasks like variant effect prediction and sequence embedding.