ClinResolve: An Explainable Clinical Evidence Reconciliation Engine using Model Context Protocol (MCP)

About this project

ClinResolve is an MCP-powered clinical decision support server that helps healthcare professionals make safer medication decisions by reconciling evidence from multiple trusted medical sources instead of relying on a single API or AI model. Traditional clinical assistants often provide recommendations without clearly explaining how a decision was reached or how conflicting medical evidence was resolved. ClinResolve addresses this challenge through an Evidence Reconciliation Engine that collects information from multiple clinical evidence providers, evaluates agreement and conflicts between sources, incorporates patient-specific context, and generates transparent, explainable medication recommendations. Built using the NitroStack MCP Framework, ClinResolve demonstrates the complete capabilities of the Model Context Protocol by combining Tools, Resources, and Prompts into a unified clinical workflow. The server provides five core MCP tools: List Patients – Browse available patient records. Select Patient – Retrieve detailed patient profiles. Collect Evidence – Gather medication evidence from multiple clinical sources. Generate Decision – Produce explainable medication recommendations (Approve, Caution, or Avoid). Audit History – Review previous clinical decisions for traceability. MCP Resources provide structured clinical context, including patient profiles, hospital policies, clinical guidelines, drug knowledge, and historical audit records, while reusable Prompts support evidence summarization and decision explanation. Rather than functioning as a chatbot, ClinResolve acts as an AI-powered clinical decision engine that emphasizes transparency, explainability, and evidence-based reasoning. Every recommendation is accompanied by supporting evidence, conflicting evidence, missing information, and a clear rationale, enabling clinicians to understand why a recommendation was generated before making a final decision. By leveraging the Model Context Protocol, ClinRe