How tarakaramaraoperabattula/elderly-care-assistant works
The product is an elderly-care assistant that handles medication questions and doctor appointments. Its main workflow checks for pending user confirmation, screens new requests for privacy and injection risks, delegates approved queries to specialist agents, and routes proposed changes through an approval gate before updating session state. The README documents the workflow and MCP capabilities; sampled source confirms the security, confirmation, state-update, and MCP setup. Specialist tool wiring and some workflow details are documented but not fully visible in the excerpts.
Main entry points: agent.py Orchestrator · mcp_server.py MCP server · agent_runtime_app.py Agent Engine app · telemetry.py Telemetry setup
Components 20
Conversation workflow
- Confirmation handler
app/agent.py - Security checkpoint
app/agent.py - Security alert
app/agent.py - Orchestrator
app/agent.py - Action router
app/agent.py - Approval gate
app/agent.py - Final response
app/agent.py - Session state
app/agent.py
Care specialists
- Medication agent
app/agent.py - Appointment agent
app/agent.py
MCP domain tools
- MCP server
app/mcp_server.py - Medication warnings
app/mcp_server.py - Doctor directory
app/mcp_server.py - Appointment reminders
app/mcp_server.py
Agent runtime
- Agent Engine app
app/agent_runtime_app.py - Telemetry setup
app/app_utils/telemetry.py - Feedback model
app/app_utils/typing.py
Other components
- User
- Cloud Logging
- Cloud Storage
Connections 23
- User → Confirmation handler: sends message
- Confirmation handler → Security checkpoint: new request
- Confirmation handler → Final response: confirmed reply
- Security checkpoint → Security alert: blocks request
- Security checkpoint → Orchestrator: approves request
- Security alert → Final response: returns alert
- Orchestrator → Medication agent: delegates medication
- Orchestrator → Appointment agent: delegates appointment
- Orchestrator → Action router: passes output
- Action router → Approval gate: requires approval
- Action router → Final response: direct response
- Approval gate → Final response: requests confirmation
- Confirmation handler → Session state: updates confirmed action
- Medication agent → MCP server: uses MCP
- Appointment agent → MCP server: uses MCP
- MCP server → Medication warnings: dispatches tool
- MCP server → Doctor directory: dispatches tool
- MCP server → Appointment reminders: dispatches tool
- Agent Engine app → Orchestrator: hosts workflow
- Agent Engine app → Telemetry setup: sets up telemetry
- Agent Engine app → Feedback model: validates feedback
- Agent Engine app → Cloud Logging: logs feedback
- Telemetry setup → Cloud Storage: uploads telemetry