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Ascent: An Agentic System over the Model Context Protocol for Real-World Clinical Data Analysis

arXiv cs.AI Medical/Healthcare AI Angelo Ziletti, Leonardo D'Ambrosi, Melanie Tuchardt, Tim Kondziella 2026-09-21
Representative image for Ascent: An Agentic System over the Model Context Protocol for Real-World Clinical Data Analysis

TL;DR - Ascent is an MCP-based agentic system for answering epidemiological questions from real-world clinical data using medical coding, schema-aware SQL, and cohort-analysis tools. Capable agent models substantially outperform a fixed pipeline, but require more tool calls and longer runtimes.

  • Supports both standardized and native clinical-data schemas through a shared Model Context Protocol tool interface.
  • Introduces EpiTrap, a dataset testing whether systems avoid recognized pharmacoepidemiological errors.
  • Agents improve accuracy over the fixed pipeline by an average of 27 percentage points on native schemas and 20 points on standardized schemas.
  • Real-project experience suggests value for feasibility assessment, iterative diagnosis, and expert-guided analysis.

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