"Executing Orders on Alpaca Trading Platform" matching MCP servers:

Enables AI assistants to interact with the Open Targets Platform API to search and retrieve comprehensive data about target-disease associations, drugs, genes, and drug discovery information through GraphQL queries.

A clean-room SHARP-on-MCP compliant FHIR R4 MCP server that enables AI agents to interact with any FHIR R4 endpoint using SHARP context headers, without server-side OAuth. It provides clinical tools, lab results, imaging, and interactive MCP-UI dashboards.

Integrates healthcare data from multiple sources (HL7 v2, FHIR, DICOM, device telemetry) and provides clinicians with secure, role-based access to patient context, care unit summaries, device events, diagnostic exams, and other clinical data through specialized MCP tools.

A learning MCP server providing synthetic FHIR patient data with read tools and a gated write workflow (propose → human approve → commit) with structured audit logging.

MCP server enabling AI agents to search and retrieve evidence reviews from evipedia.ai on health and longevity interventions, and to suggest new interventions for review.

Enables AI assistants to query and read data on DICOM servers (PACS, VNA, etc.).

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.

Provides seamless integration with FHIR APIs, enabling AI/LLM tools to search, retrieve, and analyze clinical healthcare data with support for SMART-on-FHIR authentication and multiple transport protocols.

Enables conversational access to 400,000+ clinical trials on ClinicalTrials.gov, allowing users to search, compare, and retrieve trial details using plain English through MCP-compatible clients like Cursor and Claude Desktop.

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

Provides deterministic parental guidance for children with chronic kidney disease, including food safety checks, lab report interpretation, and nutrient-aware food substitutions based on authoritative guidelines and the Chinese Food Composition Table.

MCP server for pediatric CKD follow-up management, providing tools to schedule follow-ups based on KDIGO 2024 guidelines, retrieve follow-up records, compute adherence scores, and access PEW history.

Generates multi-day CKD meal plans for children based on PRNT targets (energy, protein, potassium, phosphorus, sodium), providing nutrient summaries and target achievement rates for dietitians.

Enables interaction with FHIR APIs, specifically for Oracle Millennium Platform, providing tools to access and manage healthcare data such as patient records, clinical data, and administrative information.

Enables publishing of medical content (articles, procedures, clinics) to a Korean skincare platform via a publishing API, requiring API URL and API key for authentication.

Enables AI-driven pharmacogenomic analysis by querying structured genetic variant, drug response, and disease risk data. Supports natural language questions about medications, traits, and health risks based on user genome data, with privacy-first local execution.

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.

Enables bioinformatics analysis through natural language conversations with Claude Desktop, automatically generating and executing Python scripts to produce HTML reports and visualizations.

MCP server that locally de-identifies health documents, such as prescriptions, reports, images, and PDFs, before use with Codex or Claude Code. It runs OCR and identifier detection on-device and only returns de-identified text to the agent when the automated policy check results in PASS.

Enables read-only SMART on FHIR R4 discovery, search, and read operations against public synthetic sandboxes, returning actual empty results and 404s rather than inventing patient data.