"Red" matching MCP servers:

MCP server for real-time querying of the Bradesco Saude referenced network, exposing a search_providers tool to search for doctors, hospitals, clinics, and labs.

Privacy layer for healthcare AI agents. Pseudonymises patient identifiers (NHS numbers, names, dates of birth, addresses; UK and US) into labelled tokens locally before text reaches an agent, then restores the originals afterwards, keeping the token map out of agent context.

Enables AI coding agents to perform end-to-end medical image analysis locally, from inspecting CT/MRI/X-ray studies and running containerized segmentation models like MedSAM2, TotalSegmentator, and HD-BET to refining masks, measuring volumes, and writing reports. It pairs preset or custom guideline protocols with a code-customizable viewer that renders images back to agents as annotated PNGs and to humans as interactive HTML.

Enables LLM agents to connect to and control OPC UA LADS laboratory instruments, with approval-gated execution of state-changing operations and retrievable SHA-256 witnessed provenance records.

Analyzes clinical trial site feasibility, enrollment velocity, eligibility criteria, and benchmark performance across ClinicalTrials.gov's registry via a structured MCP interface.

Enables AI agents to access FDA and ClinicalTrials.gov data for medical device compliance, adverse event monitoring, and regulatory due diligence.

Exposes the Redix AnyToAny healthcare data conversion engine to AI agents, enabling conversion between X12, FHIR, HL7 v2, CDA, and other formats via the Model Context Protocol.

Enables LLMs and AI agents to query a biomedical knowledge graph stored in RedisGraph, with tools for concept search, synonym enrichment, and study variable discovery through semantic relationships.