A comprehensive Python framework for deploying persistent AI agents on Azure AI Foundry with native support for hosted tools and MCP servers.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install agent-framework-azure-ai-py
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install agent-framework-azure-ai-py using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Agent Framework Azure Hosted Agents?
This skill focuses on the Microsoft Agent Framework Python SDK, a robust toolset designed for building and managing persistent agents within the Azure AI Foundry ecosystem. By utilizing the AzureAIAgentsProvider, developers can create agents that maintain state across conversation threads, integrate seamlessly with Azure Identity for secure authentication, and leverage high-performance models like GPT-4o. When using Openclaw Skills to implement this framework, you gain the ability to deploy enterprise-ready agents that are both scalable and deeply integrated with the Microsoft cloud stack.
The framework is particularly valuable for developers needing to bridge the gap between local development and cloud-hosted agentic workflows. It provides a standardized way to handle tools, memory, and model interactions, ensuring that your Openclaw Skills implementations remain maintainable and powerful.
Agent Framework Azure Hosted Agents Use Cases
- Creating persistent customer support bots that retain history through AgentThreads.
- Automating complex data analysis using the Hosted Code Interpreter tool.
- Building research assistants that combine Bing Web Search with internal document retrieval via File Search.
- Developing multi-agent systems that communicate through Model Context Protocol (MCP) integrations.
- Implementing real-time streaming interfaces for interactive AI applications.
How Agent Framework Azure Hosted Agents Works
- Authentication is established using AzureCliCredential or DefaultAzureCredential to connect to the Azure AI project.
- The AzureAIAgentsProvider is initialized to manage the lifecycle of agents and threads on the Azure AI service.
- An agent is created or retrieved, defined by specific instructions, a model deployment name, and a set of tools.
- Tools are registered, ranging from standard Python functions to hosted services like code interpreters or search engines.
- The agent executes tasks via the run or run_stream methods, often within an AgentThread to maintain persistent conversation context.
Agent Framework Azure Hosted Agents Setup
To start building with these Openclaw Skills, install the necessary Python packages and configure your Azure environment:
# Install the framework
pip install agent-framework --pre
# Configure your Azure AI Project details
export AZURE_AI_PROJECT_ENDPOINT="https://<project>.services.ai.azure.com/api/projects/<project-id>"
export AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o-mini"
Agent Framework Azure Hosted Agents Data Schema & Taxonomy
The framework organizes its operations into several key entities to ensure data persistence and structured interactions:
| Component | Description |
|---|---|
| AzureAIAgentsProvider | The primary entry point for managing agents and authentication. |
| Agent | A persistent object in Azure AI Foundry containing the system prompt and tool configuration. |
| AgentThread | A dedicated object for managing the state and history of a specific conversation. |
| Hosted Tools | Managed services including HostedCodeInterpreterTool and HostedWebSearchTool. |
| Structured Output | Pydantic-based schemas used to validate and parse agent responses into JSON. |
Agent Framework Azure Hosted Agents Advanced Features
- Support for Service-managed MCP via HostedMCPTool and Client-managed MCP via MCPStreamableHTTPTool.
- Advanced conversation persistence allowing for long-term state management across different sessions.
- Native streaming support for low-latency, chunked response delivery.
- Built-in integration with Azure Identity for secure, credential-less authentication in production environments.
- Automated function conversion, where standard Python functions are automatically transformed into Azure-compatible tools.
SKILL.md
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