Microsoft Agent Framework
Microsoft's framework for building production-grade agentic AI on Azure, now with a Go SDK option.
A structured choice for .NET, Python, and now Go developers already on Azure who need scalable, production-grade agent orchestration. The recent Go support and Agent Harness release show active evolution. Not ideal if you need low-code or extensive third-party integrations — you're locking into Microsoft's ecosystem. Consider LangChain or Semantic Kernel if you want broader community and portability.
Verified 1d ago · liveness 65/100 · cite: rightaichoice.com/tools/microsoft-agent-framework
- Enterprise developers building agentic AI on Microsoft Azure
- Teams migrating from Autogen or Semantic Kernel
- Developers needing structured workflow execution and state management
- Organizations requiring built-in multi-turn conversation and memory
- Teams seeking a low-code or no-code agent builder
- Developers needing extensive pre-built third-party integrations
- Organizations wanting an open-source, community-driven framework
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Skip Microsoft Agent Framework if you need a low-code agent builder, extensive third-party integrations, or prefer a vendor-neutral open-source ecosystem—this locks you into Microsoft's stack.
As a Microsoft Learn documentation project, Agent Framework itself is free to use; you pay for Azure resources (compute, storage) when hosting. This fits enterprises already on Azure, and is more cost-effective than many commercial agent platforms, but there are no support SLAs beyond standard Azure terms.
In short
Microsoft Agent Framework — Microsoft's framework for building production-grade agentic AI on Azure, now with a Go SDK option. Best for Enterprise developers building agentic AI on Microsoft Azure, Teams migrating from Autogen or Semantic Kernel, Developers needing structured workflow execution and state management. Paid pricing.
Viability Score
How well maintained and how widely used is Microsoft Agent Framework? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: August 2026
How we score →Key Features
- Multi-turn conversation support
- Memory and persistence management
- Workflow execution with executors and edges
- Tool integration for agents
- Agent skills customization
- Provider-based architecture
- Durable Extension integration
- A2A protocol for agent-to-agent communication
- DevUI for development and testing (Agent Harness)
- Python SDK
- Go SDK (2026)
- GitHub sample repositories
- Self-hosting and Azure Functions hosting
- Migration guides from Autogen and Semantic Kernel
- Comprehensive step-by-step getting started guides
About Microsoft Agent Framework
Microsoft Agent Framework is a developer-first platform for building structured, production-ready agentic AI systems that are deeply integrated with Azure. It guides you from creating your first agent to hosting at scale with step-by-step tutorials across seven stages. The framework supports multi-turn conversations, memory and persistence management, and workflow execution via executors and edges. Key integrations include Microsoft's Durable Extension for reliable background execution and the A2A (Agent-to-Agent) protocol for inter-agent communication. You can customize agents with tools and skills, and leverage a provider-based architecture for flexibility. The framework includes a DevUI for development and testing (now available as the Agent Harness), and offers Python, C#, and now Go SDKs, with sample repositories on GitHub. Migration guides are available for teams moving from Autogen or Semantic Kernel. Compared to open-source alternatives like LangChain, Agent Framework offers tighter Azure integration and a more opinionated structure for enterprise scenarios, but at the cost of portability and community breadth. Recent 2026 developments include the release of the Agent Harness and Microsoft's adoption of Go for AI agents, aligning with Google's approach.
Behind the Verdict
Microsoft Agent Framework is a deliberate, opinionated platform for building agentic AI in enterprise environments, particularly where Azure is the cloud foundation. Its main strength is the end-to-end guidance it provides: a seven-step path from 'Your First Agent' to 'Host Your Agent,' covering conversations, memory, workflows, and testing. The workflow execution model (executors and edges) is more structured than LangChain's free-form chains, which can be a benefit for teams that need predictability and governance. The recent release of the Agent Harness (a DevUI for local testing) and the addition of Go support signal that Microsoft is investing in developer experience and broadening its language appeal. However, the framework is still maturing (GA was expected Q1 2026), so documentation and tooling may not be as polished as more established alternatives. A significant weakness is the limited integration with non-Microsoft services; if your stack is multi-cloud or uses many third-party SaaS, you'll find less out-of-the-box support compared to LangChain's vast ecosystem. Also, there's no low-code option—everything requires coding, which may exclude business analysts and other non-developers. For enterprises already committed to Azure and Microsoft's ecosystem, this framework is a strong, coherent choice. For startups or teams that value portability and community breadth, LangChain or Semantic Kernel might be more flexible, though you'll lose the deep Azure integration and structured workflow model.
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Real-world workflow fit
Concrete scenarios for the personas Microsoft Agent Framework actually fits — and what changes day-one when you adopt it.
You need to build a customer support agent that can handle multi-turn conversations and escalate to a human.
Outcome: Follow Steps 1-2 to create the agent and add tools, then Step 3 for multi-turn, Step 4 for memory, Step 5 for workflows, Step 6 for testing with Agent Harness, and Step 7 to host on Azure Functions. You'll have a working agent in a day.
You have an existing Semantic Kernel agent and need to move to Agent Framework for better workflow structure.
Outcome: Use the provided migration guide to refactor your agent, leveraging the structured executors and edges. You'll reuse your existing tools and skills, and gain Azure integration benefits.
You want to orchestrate multiple agents using the new Go SDK and the A2A protocol.
Outcome: Use the Go SDK to write agents with inter-agent communication via A2A. The Agent Harness helps test locally before deploying to Azure Functions for scale.
Use Cases
- Build a customer support agent that handles multi-turn conversations and escalates to human agents
- Create a code review agent that analyzes pull requests and suggests improvements
- Orchestrate a fleet of agents for automated data pipeline management
- Develop a personal assistant agent that integrates with Microsoft 365 to manage calendars and emails
- Implement a multi-agent workflow for supply chain optimization
- Build a research assistant that summarizes documents and answers follow-up questions
Models Under the Hood
as of 2026-07-31
Limitations
- The framework is aimed at developers and requires coding skills; no low-code alternative exists.
- Integration depth with non-Microsoft services is minimal.
- The framework is still evolving (GA was expected Q1 2026), so documentation and tooling may mature further.
- As of 2026, Go support is new and may have fewer examples than Python or C#.
as of 2026-07-31
Verification history
We have re-verified Microsoft Agent Framework 14 times since . Each pass re-reads the vendor's own pages and updates only what actually changed.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 14 verification passes.
Free to cite with attribution — this page re-verifies continuously.
Where the pricing makes sense
The company stage and team size where Microsoft Agent Framework's pricing actually pencils out — and where peers do it cheaper.
As a Microsoft Learn documentation project, Agent Framework itself is free to use; you pay for Azure resources (compute, storage) when hosting. This fits enterprises already on Azure, and is more cost-effective than many commercial agent platforms, but there are no support SLAs beyond standard Azure terms.
Setup time & first value
How long it actually takes to get something useful out of Microsoft Agent Framework — broken out by persona, not the marketing-page minute.
For a Python or C# developer familiar with AI concepts: roughly 1 day to create a basic agent with tools, and a few days to implement workflows and test with Agent Harness. Go developers may take slightly longer due to newer SDK documentation.
Switching to or from Microsoft Agent Framework
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Autogen: Use the official migration guide to transition your agents to Agent Framework's structured workflows.
- →From Semantic Kernel: Follow the migration guide to adopt executors and edges for workflow execution.
Integrations
Resources & Guides
- Resourcelearn.microsoft.com
Agent Framework documentation
Agent Framework documentation.
- Resourcelearn.microsoft.com
Microsoft Agent Framework Overview
Build AI agents and multi-agent workflows in .NET and Python with Microsoft Agent Framework.
- Resourcelearn.microsoft.com
Microsoft Agent Framework Workflows
Overview of Microsoft Agent Framework Workflows.
Official links
Tools that pair well with Microsoft Agent Framework
Common stack mates teams adopt alongside Microsoft Agent Framework, with the specific reason each pairing earns its keep.
Alternatives to Microsoft Agent Framework
View all
Semantic Kernel
Microsoft's open-source SDK for building production-grade AI agents with plugins and orchestration.
Mastra
TypeScript framework for building production AI agents with built-in observability.
CopilotKit
Frontend stack for building agentic UX with generative UI in React
Frequently Asked Questions
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