Microsoft Agent Framework Review, Pricing & Alternatives (2026)

Microsoft maintained two agent frameworks for years. Semantic Kernel, launched in 2023, was the enterprise SDK for adding language models to C#, Python and Java apps, with plugins, planners and telemetry. AutoGen, from Microsoft Research, pioneered multi-agent conversation patterns such as group chat. In October 2025 Microsoft introduced Agent Framework to merge them, describing it as Semantic Kernel v2.0 built by the same team. It reached Release Candidate in February 2026 and version 1.0 for.NET and Python on April 3, 2026, with stable APIs and long-term support. Microsoft says Semantic Kernel v1.x will get critical fixes for at least a year after Agent Framework's general availability.

The core abstraction is an agent built around a model client, instructions and tools. Function tools are defined with type-safe decorators or attributes, and hosted tools add code interpreter and web search. A middleware pipeline intercepts agent calls for content safety, logging and compliance without changing prompts. Pluggable memory supports conversation history, key-value state and vector retrieval, with backends including Foundry Agent Service, Mem0, Redis and Neo4j. Agents and workflows can be declared in YAML files under version control. First-party connectors cover Microsoft Foundry, Azure OpenAI, OpenAI, Anthropic Claude, Amazon Bedrock, Google Gemini, GitHub Copilot and Ollama, so the framework is not tied to Azure.

Workflows are the main addition over Semantic Kernel. A graph-based engine composes agents and functions into deterministic processes that branch on conditions, run steps in parallel and merge results, with checkpointing so long-running jobs survive interruptions. Multi-agent orchestration patterns carried over from AutoGen and Microsoft Research include sequential, concurrent, handoff, group chat and Magentic-One, all with streaming, human-in-the-loop approvals and pause and resume. For interoperability, agents can call tools on MCP servers, coordinate with agents in other frameworks over the A2A protocol, and stream to front ends through AG-UI. Migration assistants analyze Semantic Kernel or AutoGen code and generate migration plans.

The framework is free and open source under the MIT license, with packages on NuGet and PyPI and source on GitHub. Costs come from the models and services you connect: tokens from Azure OpenAI, OpenAI, Anthropic or other providers, plus any Azure resources such as Foundry Agent Service, Cosmos DB or Azure AI Search. Developers can run agents locally with Ollama at no model cost. Microsoft offers support for production deployments through Azure support plans rather than a separate license. Java support, which Semantic Kernel had, is not part of the 1.0 release, which covers.NET and Python only.

Agent Framework suits.NET and Python teams, especially those on Azure, that want typed APIs, telemetry and governance in agent code. Its drawbacks are churn for teams that adopted Semantic Kernel or AutoGen, a young community compared with LangChain, and documentation that assumes Microsoft services. LangGraph from LangChain offers similar graph workflows with a large Python and JavaScript community. CrewAI focuses on role-based agent crews, the OpenAI Agents SDK is a lightweight option tied to OpenAI's APIs, and Google's Agent Development Kit serves Gemini users. Choose Microsoft Agent Framework if you build in C# or Python and want an enterprise-supported path from prototype to multi-agent production.