Introducing the Microsoft Agent Framework

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Introducing the Microsoft Agent Framework: A Unified Foundation for AI Agents and Workflows

The landscape of AI development is evolving rapidly, and Microsoft is at the forefront with the release of the Microsoft Agent Framework an open-source SDK designed to empower developers to build intelligent, multi-agent systems with ease and precision. Whether you're working in .NET or Python, this framework offers a unified, extensible foundation that merges the best of Semantic Kernel and AutoGen, while introducing powerful new capabilities for agent orchestration and workflow design.

Why Another Agent Framework?

Both Semantic Kernel and AutoGen have pioneered agentic development, Semantic Kernel with its enterprise-grade features and AutoGen with its research-driven abstractions. The Microsoft Agent Framework is the next generation of both, built by the same teams to unify their strengths:

• AutoGen’s simplicity in multi-agent orchestration.
• Semantic Kernel’s robustness in thread-based state management, telemetry, and type safety.
• New capabilities like graph-based workflows, checkpointing, and human-in-the-loop support

This convergence means developers no longer have to choose between experimentation and production. The Agent Framework is designed to scale from single-agent prototypes to complex, enterprise-ready systems

Core Capabilities

🧠 AI Agents

AI agents are autonomous entities powered by LLMs that can process user inputs, make decisions, call tools and MCP servers, and generate responses. They support providers like Azure OpenAI, OpenAI, and Azure AI, and can be enhanced with:

• Agent threads for state management.
• Context providers for memory.
• Middleware for action interception.
• MCP clients for tool integration

Use cases include customer support, education, code generation, research assistance, and more—especially where tasks are dynamic and underspecified.

🔄 Workflows

Workflows are graph-based orchestrations that connect multiple agents and functions to perform complex, multi-step tasks. They support:

• Type-based routing
• Conditional logic
• Checkpointing
• Human-in-the-loop interactions
• Multi-agent orchestration patterns (sequential, concurrent, hand-off, Magentic)

Workflows are ideal for structured, long-running processes that require reliability and modularity.

Developer Experience

The Agent Framework is designed to be intuitive and powerful:

• Installation:
  • Python:

  pip install agent-framework

  • .NET:

  dotnet add package Microsoft.Agents.AI
  

Integration:

• Works with Foundry SDK, MCP SDK, A2A SDK, and M365 Copilot Agents

• Samples and Manifests:

  • Explore declarative agent manifests and code samples

• Learning Resources:

  • Microsoft Learn modules
  • AI Agents for Beginners
  • AI Show demos
  • Azure AI Foundry Discord community

Migration and Compatibility

If you're currently using Semantic Kernel or AutoGen, migration guides are available to help you transition smoothly. The framework is designed to be backward-compatible where possible, and future updates will continue to support community contributions via the GitHub repository.

Important Considerations

• The Agent Framework is in public preview. Feedback and issues are welcome on the GitHub repository.
• When integrating with third-party servers or agents, review data sharing practices and compliance boundaries carefully.

The Microsoft Agent Framework marks a pivotal moment in AI development, bringing together research innovation and enterprise readiness into a single, open-source foundation. Whether you're building your first agent or orchestrating a fleet of them, this framework gives you the tools to do it safely, scalably, and intelligently.

Ready to get started? Download the SDK, explore the documentation, and join the community shaping the future of AI agents.

Read more at

Introducing Microsoft Agent Framework: The Open-Source Engine for Agentic AI Apps
Azure AI Blog - Microsoft Agent Framework

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