"Repository information for My-FastMCP-Development-Assistant-MCP on GitHub" matching MCP servers:

Retrieves comprehensive patient information including personal details, insurance plans, and employee data through the get_patient tool. Supports Docker Compose deployment and integration with Watson Orchestrate for healthcare data access.

Provides medical evidence tools including PubMed search, citation verification, clinical trial lookup, drug information, drug interaction checking, PICO extraction, and medical entity recognition via MCP.

Enables AI assistants to query ClinicalTrials.gov and PubMed for research evidence, and to compare regulatory document changes against internal files, with strict read-only access and no ability to modify or export data.

Enables AI-powered medical information retrieval through FHIR clinical document search and GraphRAG-based exploration of medical entities and relationships. Combines vector search with knowledge graph queries for comprehensive healthcare data analysis.

An MCP server that provides access to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, offering 30 tools for searching and analyzing biological data like pathways, genes, and compounds. It supports integration with LangChain and Ollama to enable LLMs to interact with comprehensive genomic and chemical datasets.

Role-based AI assistant for hospital workflows, patient FAQ, staff tools, and secure document approvals with MCP-style tool access.

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.

A clean-room SHARP-on-MCP compliant FHIR R4 MCP server that enables AI agents to interact with any FHIR R4 endpoint using SHARP context headers, without server-side OAuth. It provides clinical tools, lab results, imaging, and interactive MCP-UI dashboards.

Provides 12 medical tools for symptom checking, lab report explanation, emergency detection, and health advice, emphasizing safety and disclaimers.

Enables AI agents to query and analyze FDA adverse events, drug labels, medical device clearances, and other public health datasets through natural language commands.

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.

Provides seamless access to UniProtKB protein data, enabling querying of protein entries, sequences, Gene Ontology annotations, and ID mappings through a typed, resilient interface.

Enables querying clinical trial data from the AACT database (ClinicalTrials.gov) using natural language through tools like list_tables, describe_table, and read_query.

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

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

A unified MCP server for biomedical research that connects AI systems to resources like Ensembl, EuropePMC, STRING, and more, enabling retrieval of verified domain-specific information.

An MCP server and web application that enables natural language medical queries and patient data analysis powered by Gemini AI. It allows users to track and analyze patient biometrics, including vitals, sleep patterns, and laboratory results, through a comprehensive set of automated medical tools.

Enables LLMs to interact with OpenEHR electronic health record systems by retrieving clinical archetypes, generating AQL queries from natural language, and executing queries against on-premise EHR databases. Supports OpenEHR Clinical Knowledge Manager integration and custom IIS-hosted EHR APIs for comprehensive medical data access.

Enables medical image analysis, structured medical report generation, and medical Q\&A through the Lingshu medical AI model. Provides healthcare professionals and developers with AI-powered medical assistance capabilities via a FastMCP server interface.

Enables querying medical documents stored in Qdrant using semantic retrieval, allowing users to search PubMed articles through the Model Context Protocol.