ChatSpatial: Schema-Enforced Agentic Orchestration for Reproducible and Cross-Platform Spatial Transcriptomics

Abstract

Spatial transcriptomics analyses often require coordinating specialized Python and R methods. When analytical intent is translated through ad hoc scripts or unconstrained LLM generated code, workflows can be difficult to inspect, rerun, or compare. We present ChatSpatial, a schema enforced orchestration framework in which an LLM selects versioned tools and parameters rather than executable code. Built on the Model Context Protocol, ChatSpatial integrates 65 methods across 15 analytical categories into 20 typed tools with curated defaults. In two cancer case studies, ChatSpatial coordinated cross ecosystem workflows that recovered the analytical structure and central conclusions of published ovarian cancer and oral squamous cell carcinoma analyses. Across three LLMs, schema enforcement raised parameter validity from 20% to 98% and stabilized method selection. In end to end benchmarks against two code generation alternatives, it yielded higher execution success and output concordance.