"Methods or tools to control a computer system" matching MCP servers:

Enables LLM agents to query de-identified FHIR-shaped hospital data through audited, read-only tools for patients, encounters, conditions, observations, medications, and interaction checks, while any medication write stays a draft that a clinician must confirm out-of-band.

Enables clinical question answering via OpenEvidence with citation verification, including tools to ask questions, retrieve results, and follow up, plus an integrated skill to check citations against primary sources.

Enables MCP-capable AI clients to characterize proteins end to end: PDB/mmCIF validation, sequence extraction and typing, pLDDT confidence summaries, metal-site geometry with bidentate chelate detection, GROMACS trajectory metrics and plots, and live UniProt, AlphaFold DB, and RCSB lookups. Also ships a point-and-click Protein Lab web UI (and a persistent run registry) so students and wet-lab biologists can get the same results without any client setup.

Enables ingestion of HL7 v2, ASTM, and JSON control results, Westgard multirule evaluation, automatic patient-result holds, explainable root-cause investigation, and supervisor-approved CAPA workflows for clinical laboratories. Agents can also establish targets, compute Levey-Jennings and sigma statistics, and verify corrective actions before a supervisor lifts a hold.

Provides in-process RDKit cheminformatics operations — descriptors, fingerprints, similarity and substructure search, reaction enumeration, standardization, and 3D conformer generation — for AI agents.

Enables AI assistants to read COVID-19 lateral flow test results from photographs by calling a deployed computer-vision pipeline, returning verdicts like positive or negative with confidence.

Enables natural-language querying of a mock legacy healthcare database and returns validated FHIR resources (Patient, Observation, Condition).

A production-grade MCP server that enables AI assistants to securely manage healthcare data through clinical tools for patient vitals, lab results, and medication ordering. It prioritizes security and compliance with features like HIPAA-ready audit logging, PII redaction, and role-based access control.

Provides FHIR resource validation, synthetic test fixture generation, and HIPAA-safe logging review as MCP tools for AI agents.

A Claude Code extension that embeds a senior athenahealth integration engineer in your development workflow, proactively catching data loss bugs and guiding safe DataView queries and API integrations.

Provides GPU-accelerated scientific computing capabilities including symbolic mathematics, quantum wave mechanics simulations, molecular dynamics, and neural network training through four specialized MCP servers.

Enables deep probabilistic analysis of single-cell omics data using scvi-tools through natural language. Supports SCVI for scRNA-seq analysis, SCANVI for cell type annotation, TOTALVI for multi-modal RNA/protein data, and PEAKVI for scATAC-seq analysis.

A specialized MCP server for Metal-Organic Framework research that provides tools for database searching, structural optimization, and energy calculations via ASE. It enables scientific workflows by allowing users to interact with MOF data and perform chemical simulations through a standard SSE interface.

An MCP server for clinical workflows with tools for patient lookup, appointment booking, prescriptions, drug interactions, symptom triage, lab results, insurance eligibility, and telehealth, enforcing role-based access control and audit logging.

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.

End-to-end Prior Authorization decision-support system with a multi-agent AI pipeline, MCP Tool Registry, and PostgreSQL backend.

Enables genomic sequence analysis through the Evo 2 model, supporting DNA sequence scoring, embedding, generation, and variant effect prediction with multiple model checkpoints (7B, 40B, 1B parameters).

Enables AI agents to read and analyze Dexcom CGM data through tools for current glucose, recent historical readings, and glucose statistics such as time in range.

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

Enables interaction with the CEDAR (Center for Expanded Data Annotation and Retrieval) metadata repository to fetch templates and retrieve template instances. Supports querying structured metadata and biomedical data annotations through the CEDAR platform.