"Importing Excel Data into SQL Server" matching MCP servers:

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

Exposes four CMS public datasets as callable tools in Claude conversations, enabling natural-language real-world evidence analytics without SQL expertise.

Enables secure natural language querying of a clinical SQL Server database using a local Ollama model, with strict SQL validation to protect sensitive data.

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.

Enables access to a synthetic hospital dataset through MCP, supporting SSE and STDIO transports, deployable to IBM Cloud Code Engine.

Enables natural language querying of healthcare claims data by exposing a SQLite database with read-only SQL tools, allowing users to ask questions in plain English and get answers backed by real database queries.

Source-provenanced US federal healthcare provider data over MCP. Resolve any NPI or CCN across NPPES, OIG LEIE, SAM.gov, state Medicaid exclusions, CMS PECOS, Care Compare, and Open Payments — every field carries a 14-field provenance contract, and an "excluded or compromised anywhere" check runs on every lookup.

Enables AI assistants to access and query ARTPARK's public health datasets including dengue epidemiology, livestock census, and FMD vaccination data through a structured 4-step workflow for data discovery and retrieval.

A remote MCP server that lets an LLM explore, query, aggregate, and benchmark the ~234 datasets in the CMS Provider Data Catalog — hospitals, dialysis facilities, nursing homes, home health, hospice, physicians, and more — in plain language.

Enables MCP-compatible AI clients to validate healthcare claims data quality by running completeness, integrity, and temporal checks on CSV files via five callable tools, including profiling and full scans.

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.

An MCP server that enables AI coding assistants to interact with Rosetta, PyRosetta, and Biotite for running RosettaScripts, validating XML, translating between Rosetta and Biotite, scoring structures, and querying documentation.

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.