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agent-developer

Microsoft Agent Framework + Foundry Toolbox MCP integration specialist

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ソース情報

リポジトリ
microsoft-foundry/build-2026-demos
ソースの最終更新活動
2026年5月31日 18:27
検出された SKILL.md の言語
英語
スター
12
フォーク
5

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SKILL.md を表示中

SKILL.md
ソースの指示 · 読み取り専用プレビュー
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: ```json {"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
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