"Proof-of-Concept Examples for Multi-Component Processes (Model Context Protocol)" matching MCP servers:

Connects to wetlab protocol resources such as protocols.io, enabling users to access and manage experimental protocols via natural language.

Enables AI clients to securely access, query, and mutate normalized user-controlled health data (e.g., from Apple Health or Supabase) through a bounded set of MCP tools, with optional OAuth and sandboxed deployment.

A multi-purpose MCP server for AI-powered healthcare assistance that processes clinical data through configurable LLM providers. Maintains webhook endpoints for patient data processing with PostgreSQL logging and OpenAPI documentation.

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

Connects AI assistants to health data via the Biological Sovereignty Protocol, with cryptographically verified user consent enforced on-chain.

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

Enables AI-powered genomic variant analysis including variant impact prediction, regulatory element discovery, and batch variant scoring. Currently operates in mock mode as a proof-of-concept awaiting the public release of Google DeepMind's AlphaGenome API.

Enables Alexa+ users to coordinate household pet care by logging feeding, medication, activity, litter, and health observations for dogs and cats, with evidence-grounded triage, Q&A, and daily briefings backed by a verified veterinary library and citations.

A Model Context Protocol server providing programmatic access to 3D protein structural data from RCSB PDB, PDBe, and UniProt, enabling search, retrieval, comparison, and analysis of protein structures.

Enables interaction with AnnData objects via the Model Context Protocol, allowing querying and manipulation of annotated data matrices for single-cell genomics.

Provides secure access to VA's VistA electronic health record system, enabling AI applications to retrieve and summarize patient medical records for clinical staff.

Enables natural language exploration of OMOP CDM databases for concept discovery, patient count queries, and cohort SQL generation with support for multiple database backends.

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.

Enables querying Brazilian PCDT clinical protocols from Conitec and generating concise, context-specific treatment summaries using a local LLM, with verified literal citations and links to official PDFs.

Enables semantic retrieval and assembly of ICD-10-CM value sets from natural language descriptions for clinical cohort definitions.

Grounds gene-nomenclature work in the HUGO Gene Nomenclature Committee (HGNC) dataset, enabling resolution of gene symbols and IDs to canonical HGNC identifiers, plus cross-references and batch operations.

An MCP server implementing the ROBINS-I V2 framework for risk-of-bias assessment in non-randomized studies, with deterministic algorithms and full provenance. It enables users to parse study documents, specify target trial results, answer signalling questions with evidence-bound quotes, and compute or override domain judgements.

Enables querying and monitoring Brazilian Federal Council of Medicine resolutions on AI, telemedicine, and electronic medical records, with a local searchable copy and official document links.

Verified ICD-10-CM code lookup & validation for AI agents — official descriptions, not guesses.

Enables natural language querying of brain volumes (NIfTI) with a fixed set of tools, returning visualizations and reproducible nilearn code.