| name | Agent Developer |
| description | Microsoft Agent Framework + Foundry Toolbox MCP integration specialist |
| tags | ["python","azure","agent-framework","mcp","foundry"] |
Agent Developer Skill
You are a specialist in building and configuring the AI agent backend for this project.
Tech Stack
- Python 3.11+
- Microsoft Agent Framework 1.0
- FastAPI + Uvicorn for the API gateway
- Azure AI Foundry SDK (
azure-ai-projects)
- Azure Identity (
DefaultAzureCredential)
Architecture
This project uses a single agent that connects to the Foundry Toolbox via one MCP endpoint. The Toolbox dispatches to individual tools (FoundryIQ, WorkIQ, custom MCP, FabricIQ) behind the scenes.
API Gateway → Single Agent → Toolbox (MCP endpoint) → Multiple Tools
Agent Modes
- Local (
AGENT_MODE=local): Agent runs in-process, connects to Toolbox MCP directly via MCPStdioTool or MCPStreamableHTTPTool
- Hosted (
AGENT_MODE=hosted): Agent deployed as container in Foundry Agent Service, Toolbox configured via Foundry project
Streaming Protocol
The gateway streams newline-delimited JSON events:
{"type": "message", "content": "chunk of text"}
{"type": "activity", "tool": "FoundryIQ", "status": "running", "detail": "Searching knowledge base..."}
{"type": "activity", "tool": "FoundryIQ", "status": "complete", "detail": "Found 3 results"}
{"type": "citation", "source": "doc-name", "url": "..."}
Activity events must surface individual tool names within the Toolbox, not just "Toolbox called".
File Organization
src/fibey/agent/
├── api_server.py # FastAPI gateway
├── main.py # Local-mode entrypoint
├── hosted.py # Hosted-mode entrypoint
├── agent.py # Agent definition + Toolbox MCP connection
└── prompts/
└── system_prompt.md
Conventions
- System prompts are stored as markdown in
prompts/ and loaded at runtime
- Use
python-dotenv for environment configuration
- All Azure auth via
DefaultAzureCredential
- Type hints on all function signatures
- Use
asyncio and async/await throughout — the agent framework is async-first
