Beyond No-Code: The Developer's Path to Microsoft 365 Agents

Copilot Studio and Agent Builder make agent creation accessible to business users and IT teams. But for engineering teams building production agents that require custom logic, non-standard integrations, or enterprise-grade reliability guarantees, the tool of choice is the Microsoft Agent Framework — a developer SDK that provides a structured, infrastructure-native way to build AI agents using Anthropic's Claude models in C# and Python.

The Microsoft Agent Framework is not widely discussed outside developer communities, but it represents the most direct path from Claude's capabilities to production enterprise deployment within the Microsoft 365 ecosystem. This article is a practical overview of what it provides and how to use it effectively.

What the Microsoft Agent Framework Provides

At its core, the framework provides an abstraction layer over the Anthropic API that integrates natively with Azure infrastructure. Rather than making raw HTTP calls to the Claude API and manually managing tool orchestration, authentication, and session state, the framework handles these concerns and lets developers focus on agent logic.

The key capabilities the framework provides include: a Claude client that handles authentication with either Anthropic API keys or Azure credentials; an agent definition model where you specify the model, instructions, and tools in a structured object; built-in support for MCP tool registration, allowing agents to call any MCP-compatible external system; hosted tool integrations for web search and code execution; extended thinking support, enabling Claude to reason through complex tasks before producing outputs; and session management for maintaining conversation history across multi-turn interactions.

Both Python and C# implementations are supported. The Python SDK is the more commonly used starting point for data-intensive agents and rapid prototyping. The C# SDK integrates naturally into .NET enterprise environments and is the preferred choice for teams building agents that will run as Azure Functions or be embedded in existing .NET applications.

Setting Up Anthropic Agents in the Framework

The setup path differs slightly depending on whether you are using the Anthropic API directly or routing through Azure Foundry.

For direct Anthropic API access, you set your ANTHROPIC_API_KEY and ANTHROPIC_DEPLOYMENT_NAME environment variables, then initialise an AnthropicClient and define your agent using the client's agent creation method. The agent definition specifies the model name, a name and description for the agent, the system prompt that governs its behaviour, the tools it has access to, and the maximum token budget for responses.

For Azure Foundry deployment — the recommended path for enterprise environments with data residency requirements — you use the AnthropicFoundryClient with your Azure resource name and credentials. The agent definition is identical; only the authentication and routing changes. This means you can develop locally against the Anthropic API and deploy to Foundry in production without changing your agent logic.

Using MCP Tools in the Framework

The framework's MCP tool support is where the most powerful integrations are built. You register MCP servers with the Claude client using the get_mcp_tool method, specifying the MCP server's name and URL. From that point, the agent automatically has access to all tools the MCP server exposes, and Claude can invoke them dynamically based on what a given task requires.

For Microsoft 365 integrations, this means pointing your agent at MCP servers that wrap Microsoft Graph API calls — giving Claude the ability to search SharePoint, read calendar data, access email, post to Teams, and interact with the full Microsoft 365 data graph. Custom internal MCP servers for proprietary business systems can be registered alongside Microsoft-native ones, allowing a single agent to coordinate across your entire technology stack.

The framework also supports web search as a hosted tool, available with a single registration call. This allows agents to augment their reasoning with live web data alongside internal enterprise data — useful for competitive research agents, market monitoring agents, and any use case where current external information is relevant.

Extended Thinking for Complex Agents

One of Claude's most powerful features for complex enterprise agents is extended thinking — the ability to reason through a problem step by step before producing a final response. The Microsoft Agent Framework exposes this capability through a thinking parameter in the agent definition, allowing you to enable it at the agent level for tasks where reasoning quality matters more than response speed.

For agents handling compliance reviews, financial analysis, complex document synthesis, or multi-step planning tasks, extended thinking significantly improves output quality. The reasoning process is visible in the agent's response stream, which is also useful for debugging agent behaviour during development.

Deploying Framework-Built Agents

Agents built with the Microsoft Agent Framework can be deployed as Azure Functions (for event-driven, serverless agent execution), as Azure Container Apps (for agents requiring persistent infrastructure), or embedded as services within existing .NET or Python applications. Once deployed on Azure, they operate within your Microsoft 365 tenant's security perimeter and can be registered with Agent 365 for governance and observability.

The combination of the Microsoft Agent Framework, Claude via Azure Foundry, MCP integrations, and Agent 365 governance gives engineering teams a complete, enterprise-grade agent development and deployment stack — with full control over every layer of the architecture.

At Trim Journey, we build production agent systems on this stack for organisations that need custom architecture rather than off-the-shelf tooling. Book a technical scoping call to discuss your agent architecture requirements.