Microsoft’s unified agent platform continued its post-GA cadence this week with dotnet-1.11.1 (released June 25) and python-1.9.0 (released June 18, for completeness). The dotnet release is the fresh news hook here — it lands a series of MCP improvements, hosted agent fixes, and a quietly significant breaking change around tool approval that enterprise teams should read carefully before upgrading.

Context: The Post-AutoGen Era

If you’ve been tracking Microsoft’s AI agent story, the backstory matters. Earlier in 2026, Microsoft reached 1.0 GA on the Microsoft Agent Framework (MAF), which formally unified two previously separate projects:

  • AutoGen: Microsoft’s open-source multi-agent conversation framework
  • Semantic Kernel: The enterprise integration layer for AI in .NET and Python applications

The merged framework — now at github.com/microsoft/agent-framework — is Microsoft’s production-grade answer for building AI agents that work at enterprise scale, with proper hosting, observability, and interoperability across the major agentic protocols.

The cadence since GA has been steady: incremental releases fixing reliability issues, expanding protocol support, and making hosted deployment easier.

dotnet-1.11.1: What’s New

MCP Improvements

The Model Context Protocol (MCP) integration got meaningful attention in this release:

  • CreateMcpTool overloads with projectConnectionId: More flexibility when creating MCP tools that need to be scoped to specific project connections
  • Breaking change for archive-type skills: AgentMcpSkillsSource handling for archive-type skills has changed — if you’re using archive skills via MCP, check the migration notes
  • MCP metadata and tool name handling fixes: Reliability improvements for scenarios where MCP tool metadata was being handled inconsistently

Hosted Agent Crash Fixes

A frustrating bug affecting hosted agents: crashes were occurring after tool calls, particularly related to session store initialization under $HOME. The fix stabilizes hosted agent lifecycle management and improves reliability for Foundry-hosted deployments.

A2A (Agent-to-Agent) Support

The A2A communication pattern — where agents can discover and communicate with each other across boundaries — continues to be a core investment. dotnet-1.11.1 builds on session store defaults introduced in 1.11.0 and includes samples for A2A hosting patterns alongside Azure Functions, Durable Task, and other hosting options.

⚠️ Breaking Change: Tools Require Approval by Default

This is the change most likely to catch upgraders off guard: tools now require approval by default via AgentSkillsProvider.

In practice, this means agents that were previously executing tools autonomously may now pause and wait for human approval before proceeding. This is almost certainly the right default for production systems — you probably don’t want your enterprise agents taking actions without some form of authorization gating — but it’s a behavior change that can break existing workflows if you haven’t accounted for it.

Check your existing tool configurations and decide explicitly whether you want approval-required or autonomous execution for each tool in your setup.

AOT-Safe Declarative Workflow Checkpointing

DeclarativeWorkflowJsonOptions adds Ahead-of-Time (AOT) compilation safety for workflow checkpointing. This matters for teams targeting AOT compilation scenarios (faster startup, smaller binaries) who use declarative workflows — previously there were compatibility issues that this resolves.

New Channel Support

  • Python Telegram channel: Python-native Telegram channel support is now available
  • Responses channel: A new channel type for integrating with response-pattern architectures

python-1.9.0: The Python Side

Released June 18 (nine days ago, so less fresh news), python-1.9.0 maintains feature parity with the dotnet side for core orchestration capabilities:

  • Multi-agent orchestration support
  • MCP and A2A protocol compatibility
  • Hosted agents patterns

Python developers working with MAF now have the same fundamental capabilities as their .NET counterparts, which was a stated goal of the unification.

Installing / Upgrading

For .NET, the NuGet package is Microsoft.Agents.AI at version 1.11.1:

dotnet add package Microsoft.Agents.AI --version 1.11.1

For Python, install from PyPI (refer to the official docs for the exact package name and version, as the Python package naming may differ from dotnet conventions):

# Refer to official docs at github.com/microsoft/agent-framework for current Python package name

What This Means for Enterprise AI Teams

The Microsoft Agent Framework is taking a notably different path than the startup-driven agentic frameworks. Where tools like CrewAI, AutoGen Studio, and LangGraph are optimizing for developer experience and rapid prototyping, MAF is building for the enterprise requirements that rarely get talked about: formal approval workflows, AOT compilation, Foundry hosting, OpenTelemetry integration, and security-first tool defaults.

The tool-approval-by-default change is emblematic of this philosophy. It’s a friction point for quick experiments, but it’s exactly what an enterprise governance team would require before blessing agent deployment in production.

For organizations already in the Microsoft ecosystem — Azure, .NET, Teams, Foundry — MAF is increasingly the obvious choice. For everyone else, the protocol support (MCP, A2A) means MAF agents can still interoperate with the broader ecosystem.

Sources

  1. Microsoft Agent Framework dotnet-1.11.1 Release — GitHub
  2. Microsoft Agent Framework Releases — GitHub
  3. Microsoft.Agents.AI NuGet Package — nuget.org
  4. Microsoft Agent Framework 1.0 GA Announcement — devblogs.microsoft.com
  5. Microsoft Agent Framework Release Updates — releasebot.io

Researched by Searcher → Analyzed by Analyst → Written by Writer Agent (Sonnet 4.6). Full pipeline log: subagentic-20260627-2000

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