"Exploring RAG through defined workspaces" matching MCP servers:

Provides FHIR Implementation Guide facts via MCP tools, enabling querying of must-support, bindings, constraints, and value-set usage from StructureDefinition artifacts for conformance and testing support.

A RAG-based MCP server for natural language querying of Brazilian healthcare manuals (SIH/SUS, SIA/SUS) and official ordinances. It provides 16 tools for semantic search, regulatory critique analysis, and retrieving data from SIGTAP and CNES.

GraphRAG MCP server for querying SNOM CT medical terminology via Neo4j, offering graph_search_concept and graph_get_related tools to search and traverse concepts and relationships.

Exposes NCBI PubMed as MCP tools for searching literature, fetching abstracts, exploring citation graphs, and finding author publications without requiring an API key.

Enables LLM agents to search biomedical literature, retrieve article details, find related papers, manage caching, and download open-access full texts through MCP with structured, agent-friendly responses.

Enables LLM-based agents to interact with FHIR healthcare data through natural language prompts, providing full CRUD operations on FHIR resources, document processing, and semantic search capabilities.

Enables discovery, inspection, and cross-referencing of Protein Data Bank structures through three RCSB APIs: search, data, and sequence coordinates.

An MCP server that exposes a DICOMweb-compliant DICOM archive to AI assistants. It lets any MCP-capable client search studies, series and instances, inspect metadata, read Structured and Encapsulated PDF Reports, and render image frames — all through natural language.

Enables conversational access to 400,000+ clinical trials on ClinicalTrials.gov, allowing users to search, compare, and retrieve trial details using plain English through MCP-compatible clients like Cursor and Claude Desktop.

Enables medical RAG queries over locally indexed PDFs via AnythingLLM, with multilingual reranking and verifiable book/page citations, for use with Antigravity or any MCP client.

Enables Claude Desktop to securely access FreeStyle LibreLink continuous glucose monitoring data, providing real-time readings, historical analysis, and health insights through natural language queries.

Integrates Diabetes:M data with Claude Desktop to access glucose readings, insulin data, food diary, and health metrics through natural language conversations.

A local-first MCP server that provides fast access to OpenEMR wiki pages, users guide, and selected API documentation through tools like search, page retrieval, and category listing.

PubCrawl provides LLMs with access to PubMed, FDA/UK drug labeling, and ClinicalTrials.gov. It enables searching literature, retrieving abstracts and full texts, comparing US and UK drug labels, and exploring clinical trials.

Enables users to store and query their own medical data—labs, medications, diagnoses, wearables, and food logs—in a local Postgres database and interact with it through any MCP client, with deterministic safety checks.

MCP server for FHIR interoperability, enabling natural language querying and manipulation of clinical data with full CRUD operations, semantic search, and RAG capabilities.

MCP server to simulate NHCX payer-side actions for testing provider integrations, enabling approval, rejection, querying, and forwarding of cases. It automates the payer workflow through tools like process case and get user role.

Enables natural language querying of Korean public medical data (data.go.kr) through MCP clients like Claude, providing tools for searching hospitals, drugs, non-payment costs, disease statistics, and more.

Enables querying simulated healthcare professional engagement data from Supabase, including HCP profiles, interactions, consent status, prescribing trends, and segment analytics through natural language.

Enables querying the WormBase database for C. elegans and nematode genomics data, including gene information, protein sequences, phenotypes, interactions, and expression patterns through natural language.