I am working on a complex application, where I need to create a Customer AI Agent for HealthCare that will respond to user queries using the required tools. There multiple tasks for the agent, getting appointment details of a patient, getting patient information’s, confirming an appointment, sending appointment details via message or whatsapp, booking an appointment etc etc.
I am using a create_agent as a supervisor and the sub-agents (defined using create_agent) as a tools provided to the supervisor and the sub-agents have tools defined on an MCP server.
I am worrying either I am doing it correctly to complete all the user required tasks or not.
Second thing is the context window size increases as user interacts with the agent for a long time.
I need expert advice, either these scenarios can be implemented this way or I need to change my approach and also what are the ways that context can be managed without loosing the information’s needed by the agent to correctly take actions and reply to the user. As it is intended to be use as a Customer Call center.
Note:
There is a constraint that we can only use Groq as model providers(currently using GPT OSS 120B).
Thanks in advance.