* Bring Hosted-Toolbox sample to parity with sibling hosting samples Adds the standard scaffolding files (.env.example, agent.yaml, agent.manifest.yaml, Dockerfile, Dockerfile.contributor) that every other 04-hosting Foundry sample ships but Hosted-Toolbox lacked. Fixes the toolbox name environment variable: reads TOOLBOX_NAME instead of the platform reserved FOUNDRY_TOOLBOX_NAME so it survives agent create, and aligns the default to my-toolset. Rewrites the README to the standard section layout with PowerShell fenced commands, and adds Using-Samples READMEs documenting why the client REPLs exist. Renames Azure AI Foundry to Foundry across the 04-hosting sample READMEs and comments for consistent product naming. * Address PR review: accurate docs and TOOLBOX_NAME in ToolboxMcpSkills - SimpleAgent README: correct the demo banner to the real per-agent URL the client prints (https scheme and the /api/projects/<project> segment). - Hosted-Toolbox Program.cs: move FOUNDRY_MODEL out of the Required block into Optional since it has a gpt-4o default and an AZURE_AI_MODEL_DEPLOYMENT_NAME fallback. - Hosted-ToolboxMcpSkills: switch the toolbox name from the reserved FOUNDRY_TOOLBOX_NAME to TOOLBOX_NAME across Program.cs, .env.example, agent.yaml, agent.manifest.yaml and README so it is deployable via the manifest, matching the other toolbox samples.
Agent Framework Samples
The agent framework samples are designed to help you get started with building AI-powered agents from various providers.
The Agent Framework supports building agents using various inference and inference-style services.
All these are supported using the single ChatClientAgent class.
The Agent Framework also supports creating proxy agents, that allow accessing remote agents as if they
were local agents. These are supported using various AIAgent subclasses.
Sample Structure
| Folder | Description |
|---|---|
01-get-started/ |
Progressive tutorial: hello agent → hosting |
02-agents/ |
Deep-dive by concept: tools, middleware, providers, orchestrations |
03-workflows/ |
Workflow patterns: sequential, concurrent, state, declarative |
04-hosting/ |
Deployment: Azure Functions, Durable Tasks |
05-end-to-end/ |
Full applications, evaluation, demos |
Getting Started
Start with 01-get-started/ and work through the numbered files:
- 01_hello_agent — Create and run your first agent
- 02_add_tools — Add function tools
- 03_multi_turn — Multi-turn conversations with
AgentSession - 04_memory — Agent memory with
AIContextProvider - 05_first_workflow — Build a workflow with executors and edges
- 06_host_your_agent — Host your agent via Azure Functions
Additional Samples
Some additional samples of note include:
- Agents: Basic steps to get started with the agent framework.
These samples demonstrate the fundamental concepts and functionalities of the agent framework when using the
AIAgentand can be used with any underlying service that provides anAIAgentimplementation. - Agent Providers: Shows how to create an AIAgent instance for a selection of providers.
- Agent Telemetry: Demo which showcases the integration of OpenTelemetry with the Microsoft Agent Framework using Azure OpenAI and .NET Aspire Dashboard for telemetry visualization.
- Durable Agents - Azure Functions: Samples for using the Microsoft Agent Framework with Azure Functions via the durable task extension.
- Durable Agents - Console Apps: Samples demonstrating durable agents in console applications.
Migration from Semantic Kernel
If you are migrating from Semantic Kernel to the Microsoft Agent Framework, the following resources provide guidance and side-by-side examples to help you transition your existing agents, tools, and orchestration patterns.
The migration samples map Semantic Kernel primitives (such as ChatCompletionAgent and Team orchestrations) to their Agent Framework equivalents (such as ChatClientAgent and workflow builders).
For an in-depth migration guide, see the official migration documentation.
Prerequisites
For prerequisites see each set of samples for their specific requirements.