Building a Multi-Agent Pipeline with the Microsoft Agent Framework
The article explores the Microsoft Agent Framework, a lightweight Python package for building AI agents with native MCP support. The author walks through the process of building a practical pipeline that reads a product backlog from a Markdown file and automatically creates Epics and Stories on Jira.
Why it matters
The Microsoft Agent Framework provides a powerful and flexible platform for building AI-powered applications, making it easier for developers to create complex, multi-agent systems.
Key Points
- 1The Microsoft Agent Framework combines features from Semantic Kernel and AutoGen, providing abstractions for single- and multi-agent patterns, session-based state management, and enterprise-grade features.
- 2The framework favors simplicity and explicitness, allowing developers to write Python functions and wire them together to control the flow of the multi-agent pipeline.
- 3The author used the core Agent class, OpenAIChatClient, MCPStdioTool, and the @tool decorator to build a working multi-agent pipeline.
Details
The Microsoft Agent Framework is the direct successor of Semantic Kernel and AutoGen, created by the same Microsoft teams. It combines AutoGen's simple abstractions for single- and multi-agent patterns with Semantic Kernel's enterprise-grade features like session-based state management, type safety, telemetry, and extensive model support. The framework also introduces workflows for explicit control over multi-agent execution paths and a robust state management system for long-running and human-in-the-loop scenarios. The author used the core Agent class, OpenAIChatClient, MCPStdioTool, and the @tool decorator to build a working multi-agent pipeline that reads a product backlog from a Markdown file and automatically creates Epics and Stories on Jira.
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