Agentic-AI Healthcare: Multilingual, Privacy-First Framework with MCP Agents
This addresses the problem of integrating AI into healthcare with privacy and multilingual support for patients and providers, but it is incremental as it builds on existing protocols and standards.
The paper tackles the challenge of creating a privacy-aware and multilingual healthcare AI system by introducing Agentic-AI Healthcare, a research prototype that uses the Model Context Protocol to orchestrate agents for tasks like symptom checking and appointment scheduling, with results demonstrating feasibility through example use cases in multiple languages.
This paper introduces Agentic-AI Healthcare, a privacy-aware, multilingual, and explainable research prototype developed as a single-investigator project. The system leverages the emerging Model Context Protocol (MCP) to orchestrate multiple intelligent agents for patient interaction, including symptom checking, medication suggestions, and appointment scheduling. The platform integrates a dedicated Privacy and Compliance Layer that applies role-based access control (RBAC), AES-GCM field-level encryption, and tamper-evident audit logging, aligning with major healthcare data protection standards such as HIPAA (US), PIPEDA (Canada), and PHIPA (Ontario). Example use cases demonstrate multilingual patient-doctor interaction (English, French, Arabic) and transparent diagnostic reasoning powered by large language models. As an applied AI contribution, this work highlights the feasibility of combining agentic orchestration, multilingual accessibility, and compliance-aware architecture in healthcare applications. This platform is presented as a research prototype and is not a certified medical device.