MARC v1: An Open-Source Multi-Agent Framework for Clinical AI Reasoning and Coordination
On the map: LLM reasoning → Clinical and biomedical applications
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Abstract (arXiv)
We present Multi-Agent Reasoning and Coordination (MARC), an open-source framework that replaces monolithic LLM prompting with deterministic multi-agent orchestration for clinical reasoning. MARC coordinates role-specialized agents for extraction, reasoning, answer generation, and evaluation, with explicit context passing and traceable intermediate outputs, enabling stage-wise failure attribution. We additionally introduce a Decomposer module that generates task-specific agent prompts from a plain-language description, eliminating manual prompt engineering. The framework supports both API-based and local CPU-compatible deployments and is entirely configurable via YAML, without code modifications. MARC is designed to be model-agnostic, interpretable, and accessible to clinical domain experts without programming expertise. The full framework is available at https://github.com/Penn-RAIL/MARC-v1.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Clinical and biomedical applications, one of 17 directions in LLM reasoning. Builds on 8 of its 22 references that are in the map. First posted on arXiv 13 Aug 2026.
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8 of 22 references.
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Same direction, newest first
- 2025Capabilities of GPT-5 on Multimodal Medical Reasoning11 Aug
- 2025Multi-step retrieval and reasoning improves radiology question answering with large language models1 Aug
- 2025RadFabric: Agentic AI System with Reasoning Capability for Radiology17 Jun
Other references · 5
- 2023Capabilities of GPT-4 on Medical Challenge Problemscited by 638
- 2025MedGemma Technical Reportcited by 436
- 2025Generative to Agentic AI: Survey, Conceptualization, and Challengescited by 33
- 2024Best Practices for Large Language Models in Radiologycited by 5
- 2025Retrieval-Augmented Generation in Medicine: A Scoping Review of Technical Implementations, Clinical Applications, and Ethical Considerationscited by 5
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