Evan Mattson
acec9caa2f
* Bump Python version for a release. * Revert lockstep bumps on unchanged connectors Per PR review: only connectors that changed (or whose published metadata changed) should get new versions. Keeps released tier at 1.1.1, a2a/ag-ui at 1.0.0b260422, foundry-hosting at 1.0.0a260422; reverts the 19 unchanged betas and 2 unchanged alphas to 1.0.0b260421/1.0.0a260421. Reverts all 26 non-core agent-framework-core floors to >=1.1.0,<2 since no connector actually depends on a 1.1.1 API or bug fix. * Restore lockstep prerelease bumps and raise core floors to >=1.1.1 Reverses the lean-revert: all beta packages stamped 1.0.0b260423 and alpha packages stamped 1.0.0a260423 (Asia date, matching release cut time). All 26 non-core packages raise agent-framework-core lower bound from >=1.1.0,<2 to >=1.1.1,<2 to signal the validated cohort for this release. CHANGELOG date updated to 2026-04-23.
Agent Framework Foundry
This package contains the Microsoft Foundry integrations for Microsoft Agent Framework, including Foundry chat clients, preconfigured Foundry agents, Foundry embedding clients, and Foundry memory providers.
Toolboxes
A toolbox is a named, versioned bundle of hosted tool configurations — code interpreter, file search, image generation, MCP, web search, and so on — stored inside a Microsoft Foundry project. Toolboxes let you manage tool configuration once and reuse it across agents.
Authoring a toolbox
Toolboxes can be authored two ways:
- Foundry portal — create and version toolboxes through the UI without touching code.
- Programmatically — use the
azure-ai-projectsSDK to create, update, and version toolboxes from Python.
Toolbox authoring APIs (
ToolboxVersionObject,ToolboxObject,project_client.beta.toolboxes.*) requireazure-ai-projects>=2.1.0. Earlier versions can only consume toolboxes that already exist.
Using toolboxes with FoundryAgent
For hosted FoundryAgent, the toolbox must already be attached to the agent in the Microsoft Foundry project. Once attached, the agent invokes its toolbox tools transparently — no client-side wiring required — and you interact with the agent the same way you would with any other tool-equipped Foundry agent.
Using toolboxes with FoundryChatClient
There are two patterns for wiring a toolbox into a FoundryChatClient-backed agent.
1. Fetch, optionally filter, and pass the tools directly
Load the toolbox from the Microsoft Foundry project, optionally select a subset of its tools, and hand them to an Agent alongside any other tools you own:
from agent_framework import Agent
from agent_framework.foundry import FoundryChatClient, select_toolbox_tools
client = FoundryChatClient(...)
toolbox = await client.get_toolbox("my-toolbox", version="3")
# Pass the whole toolbox:
agent = Agent(client=client, tools=toolbox)
# Or filter to a subset first:
selected = select_toolbox_tools(toolbox, include_types=["code_interpreter", "mcp"])
agent = Agent(client=client, tools=selected)
See foundry_chat_client_with_toolbox.py for a full example, including combining multiple toolboxes.
2. Connect to the toolbox's MCP endpoint with MCPStreamableHTTPTool
Each toolbox is reachable as an MCP server. Instead of fetching and fanning out its individual tool definitions, you can point a MAF MCPStreamableHTTPTool at the toolbox's MCP endpoint — the agent then discovers and calls its tools over MCP at runtime:
from agent_framework import Agent, MCPStreamableHTTPTool
from agent_framework.foundry import FoundryChatClient
async with Agent(
client=FoundryChatClient(...),
instructions="You are a helpful assistant. Use the toolbox tools when useful.",
tools=MCPStreamableHTTPTool(
name="my_toolbox",
description="Tools served by my Foundry toolbox",
url="https://<your-toolbox-mcp-endpoint>",
),
) as agent:
result = await agent.run("What tools are available?")
print(result.text)