Welcome to Microsoft Agent Framework!
Microsoft Agent Framework (MAF) is an open, multi-language framework for building production-grade AI agents and multi-agent workflows in .NET and Python.
Microsoft Agent Framework is built for teams taking agents from prototype to production. It provides a consistent foundation for building, orchestrating, and operating agent systems across Python, .NET and Go, while keeping architecture choices open as requirements evolve, and supports a broad ecosystem including Microsoft Foundry, Azure OpenAI, OpenAI, and the GitHub Copilot SDK, with samples and hosting patterns for both local development and cloud deployment.
[!NOTE] For the Go SDK, including its documentation, samples, contribution guidance, and issue tracker, visit microsoft/agent-framework-go.
Watch the full Agent Framework introduction (30 min)
Is this the right framework for you?
MAF is a strong fit if you:
- are building agents and workflows you expect to run in production,
- need orchestration beyond a single prompt or stateless chat loop,
- want graph-based patterns such as sequential, concurrent, handoff, and group collaboration,
- care about durability, restartability, observability, governance, or human-in-the-loop control,
- need provider flexibility so your architecture can evolve without major rewrites.
Key Features
Explore new MAF capabilities and real implementation patterns on the official blog.
- Python and C#/.NET Support: Full framework support for both Python and C#/.NET implementations with consistent APIs
- Go Support: For the Go SDK, including its documentation, samples, contribution guidance, and issue tracker, visit microsoft/agent-framework-go.
- Multiple Agent Provider Support: Support for various LLM providers with more being added continuously
- Middleware: Flexible middleware system for request/response processing, exception handling, and custom pipelines
- Orchestration Patterns & Workflows: Build multi-agent systems with graph-based workflows supporting sequential, concurrent, handoff, and group collaboration patterns; includes checkpointing, streaming, human-in-the-loop, and time-travel
- Foundry Hosted Agents (new): Deploy and host your agents to Foundry-hosted infrastructure with just 2 additional lines of code
- Observability: Built-in OpenTelemetry integration for distributed tracing, monitoring, and debugging
- Declarative Agents: Define agents using YAML for faster setup and versioning
- Agent Skills: Build domain-specific knowledge bases from multiple sources—files, inline code, class libraries—for agents to discover and use
- AF Labs: Experimental packages for cutting-edge features including benchmarking, reinforcement learning, and research initiatives
- DevUI: Interactive developer UI for agent development, testing, and debugging workflows
Table of Contents
Getting Started
Installation
Python
pip install agent-framework
# This installs the standard package set; install `agent-framework-lab` separately for experimental modules.
# It may take a minute on first install on Windows.
.NET
dotnet add package Microsoft.Agents.AI
# For Foundry integration (used in the .NET quickstart below):
dotnet add package Microsoft.Agents.AI.Foundry
dotnet add package Azure.AI.Projects
dotnet add package Azure.Identity
Learning Resources
- Overview - High level overview of the framework
- Quick Start - Get started with a simple agent
- Tutorials - Step by step tutorials
- User Guide - In-depth user guide for building agents and workflows
- Migration from Semantic Kernel - Guide to migrate from Semantic Kernel
- Migration from AutoGen - Guide to migrate from AutoGen
Quickstart
Basic Agent - Python
Create a simple Azure Responses Agent that writes a haiku about the Microsoft Agent Framework
# pip install agent-framework
# Use `az login` to authenticate with Azure CLI
import os
import asyncio
from agent_framework import Agent
from agent_framework.foundry import FoundryChatClient
from azure.identity import AzureCliCredential
async def main():
# Initialize a chat agent with Microsoft Foundry
# the endpoint, deployment name, and api version can be set via environment variables
# or they can be passed in directly to the FoundryChatClient constructor
agent = Agent(
client=FoundryChatClient(
credential=AzureCliCredential(),
# project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
# model=os.environ["FOUNDRY_MODEL_DEPLOYMENT_NAME"],
),
name="HaikuAgent",
instructions="You are an upbeat assistant that writes beautifully.",
)
print(await agent.run("Write a haiku about Microsoft Agent Framework."))
if __name__ == "__main__":
asyncio.run(main())
Basic Agent - .NET
Create a simple Agent, using Microsoft Foundry that writes a haiku about the Microsoft Agent Framework
// This sample shows how to create and run a basic agent with AIProjectClient.AsAIAgent(...).
using Azure.AI.Projects;
using Azure.Identity;
using Microsoft.Agents.AI;
string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
AIAgent agent =
new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential())
.AsAIAgent(model: deploymentName, instructions: "You are an upbeat assistant that writes beautifully.", name: "HaikuAgent");
// Once you have the agent, you can invoke it like any other AIAgent.
Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));
More Examples & Samples
Python
- [Getting St