ai-care-agent-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@ai-care-agent-mcpFind a primary care doctor in Chicago accepting Cigna"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
ai-care-agent-mcp
Headless care coordination agent: MCP tools and A2A skills for case-aware, multi-pathway provider search, powered by ai-carematch. Case-management API integration is planned for later phases.
Documentation
Spec — architecture, tools, case model, phases
Phased plan — status, workstreams, exit criteria
AWS deployment / IaC — Terraform, ECS, API Gateway
Acceptance — program and phase acceptance criteria
Project structure — repo layout and layer conventions
Related MCP server: FHIR MCP Server
Quick start
uv sync --dev --group test
cp .env.example .env # set CAREMATCH_BASE_URL
make verify
make run-mcp # stdio MCP serverLayout
src/ai_care_agent_mcp/
├── mcp/ # FastMCP tools + registry
├── carematch/ # upstream HTTP adapter
├── case/ # case profile resolution (Phase 2)
├── pathways/ # pathway catalog
├── core/ # settings, errors, logging
└── a2a/ # Agent Card (Phase 3)Status
Phase | Name | Status |
0 | Foundation | Complete |
1 | Carematch MCP MVP | In progress — schemas, OpenAPI pin, validation |
2 | Case-backed search | Planned |
3 | A2A + HTTP + AWS IaC | Planned — ECS, API Gateway, Terraform |
4 | Case-management APIs | Planned |
Details: docs/plan/phased-delivery.md.
Maintenance
Resources
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If you are the server author, to access and configure the admin panel.
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