"Understanding File Systems" matching MCP servers:

Enables quantum systems analysis and simulation including quantum circuits, open quantum systems, quantum chemistry calculations, many-body physics, quantum machine learning, and quantum field theory computations.

Works out a health plan from your own record: which screening is due and evidence-based suggestions with citations. Reads and writes one health-roadmap.json file on your machine; nothing is sent to a server.

Enables AI agents to retrieve cited pharmacogenomic and gene-variant information, including drug–gene guidance from CPIC/DPWG and rsID lookups, so responses can quote curated sources instead of relying on memory. A local package also lets users read raw DNA files on their own computer without sending the file data to the remote service.

Enables any MCP client to ask what a medical procedure costs at three Chicago hospitals and get back rows cited to each hospital's own published price file and provider registry data. Tools stay read-only and typed, returning provenance such as source file, SHA-256, effective date, and release tag with every result.

Connects DHIS2 health information systems to AI assistants via the Model Context Protocol, enabling natural language queries for analytics, metadata, and tracker data.

A Model Context Protocol (MCP) server that gives AI assistants direct access to the World Health Organization's Global Health Observatory (GHO) for comparative health systems research.

Upload your raw DNA file from 23andMe, AncestryDNA, MyHeritage, FamilyTreeDNA, or any VCF -- and watch a team of AI agents fan out across 16+ public genomics databases, share discoveries with each other in real time, and produce a comprehensive health report. Everything runs on your machine. Nothing is uploaded anywhere.

A TypeScript MCP server for interacting with CDISC Define-XML 2.0 and 2.1 files, enabling users to load, search, and retrieve clinical data metadata including datasets, variables, and codelists. It supports local file processing with document caching and provides responses in both JSON and Markdown formats.

MCP server for connecting Claude Desktop to a local medical knowledge base with real-time file watching, enabling natural language interaction with medical documents.

Enables design-correct, conversational analysis of NHANES public-use data by automating file discovery, merging, weight selection, pooling, survey variance estimation, and mortality-linked Cox models.

Model Context Protocol server for accessing Reactome pathway and systems biology data.

A comprehensive Model Context Protocol server for accessing Gene Ontology (GO) data, enabling AI systems to perform ontology-based analysis, gene annotation research, and functional enrichment studies.

Enables searching, retrieving, and downloading protein structure data from the RCSB Protein Data Bank. Supports intelligent protein structure search, comprehensive data retrieval, and multiple file format downloads for bioinformatics research.

An MCP server that provides a toolbox for interacting with EPA SWMM stormwater models, enabling users to analyze model data and interpret results through LLM-driven tools. It assists stormwater modelers in understanding hydraulic systems and modeling behavior using natural language interfaces.

Enables comprehensive interaction with DHIS2 health information systems through 40+ tools covering complete Web API functionality. Supports data management, tracker programs, analytics, and bulk operations for DHIS2 development and administration.

A local-first, model-agnostic MCP server that stores personal health data in a SQLite file and provides analysis-ready views for any AI client to log, retrieve, and reason over health records.

Provides access to Allen Institute for Neural Dynamics (AIND) metadata and data assets through MongoDB queries, aggregation pipelines, NWB file exploration, and AI-powered data summaries.

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.

Enterprise-grade MCP Server for FHIR-based EMRs. Enables AI agents to read, search, create, and update any FHIR R4 resource across major EHR systems like EPIC, Cerner, and OpenEMR.

Enables AI agents to securely interact with FHIR R4-based EMRs, supporting read, search, create, and update operations on any FHIR resource type across systems like Epic, Cerner, and OpenEMR.