MCP Getting Started
The Rhino FCP MCP Server connects any AI assistant directly to the Rhino Federated Computing Platform. Through natural language, you can run federated analytics, explore datasets, execute code, and monitor jobs — all without raw data ever leaving your sites.
This section covers everything you need to get started and use the MCP server effectively.
What You Can Do
The MCP server exposes 8 capability areas, each mapped to a set of tools your AI assistant can invoke:
Authentication
Login, confirm identity, verify connectivity
Projects
List, inspect, create, and delete federated projects
Datasets
Register, sync, profile, compare, and delete datasets — including federated datasets spanning multiple sites
Queries
Run mean, Kaplan-Meier, Cox PH, Table 1, chi-square, SQL, and more via a single unified tool
Execution
Upload Python code objects, execute them across sites, launch NVFlare training jobs
Monitoring
Check run status, stream logs, list recent runs, halt jobs
Collaboration
List, invite, and remove collaborators; check site connectivity and workgroup health
Harmonization
Manage schemas, browse vocabularies, apply semantic and syntactic mappings, run full pipelines
Privacy and Data Safety
Privacy is enforced at the platform level. All results returned by the MCP server are aggregated — raw patient data never leaves hospital sites. You will never see individual patient records through any MCP tool.
The MCP server enforces the same access permissions as the Rhino FCP platform itself. Each user authenticates with their own account and sees only the projects and data they are authorised to access.
Base URL
The MCP server endpoint is:
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