A practical guide to Microsoft Teams integrations with AgentKit (2025)

It seems like every other day there’s a new push to get AI into our work apps, and collaboration hubs like Microsoft Teams are right in the middle of it all. For developers, OpenAI's new AgentKit seems like a powerful way to build custom AI agents that live directly inside your company’s chat. It paints a picture of automated assistants for just about anything, from IT support to HR queries.

But while AgentKit is a cool toolkit for engineers, it brings up a huge question for everyone else: is a complicated, code-heavy approach the only way to get useful AI in your Teams workspace? Or are there simpler, more direct ways to get the same results (or even better ones) without needing a dedicated development team on call? Let’s break it down.

What is OpenAI's AgentKit?

First off, AgentKit isn't a product you can just download and turn on. It's a collection of tools for developers to build, deploy, and manage AI agents. Think of it less like a finished car and more like a high-tech workshop full of specialized equipment. To get any value from it, you need someone who knows how to use all the tools.

This is a really important distinction: AgentKit is made for developers. It’s built for people who are comfortable working with APIs, setting up cloud services, and writing code. It’s made up of a few key parts that have to work together.

Agent Builder: A visual canvas for workflows

The Agent Builder is a central piece of the puzzle. It gives developers a visual, drag-and-drop canvas to map out how an agent should think and act. They can create workflows, connect different tools, and set up the logic for how the agent responds to questions. It’s a neat way to visualize a complex process, but it’s still a tool for building logic from scratch, not a solution that’s ready to go.

Connector Registry: The bridge to company data

For an agent to be helpful, it needs to access your company’s information. The Connector Registry is where developers and admins manage these connections. It’s a central hub for linking the agent to data sources like Google Drive, Dropbox, and, of course, Microsoft Teams. Getting this set up correctly is a big deal for security and governance, and it takes careful administrative work to make sure the agent only sees the information it’s supposed to.

ChatKit: A build-your-own UI

Finally, once the agent is built, people need a way to talk to it. ChatKit provides the basic components for creating a chat interface that can be dropped into an application or website. This is another step that requires a technical touch, as it involves front-end development to get the chat window integrated and working smoothly.

How developers use the toolkit to build Microsoft Teams integrations with AgentKit

So, how does a developer actually make an agent built with AgentKit show up and work inside Microsoft Teams? It’s definitely not a simple one-click install. The process usually involves another specialized tool called the Microsoft 365 Agents Toolkit (which used to be the Teams Toolkit). This is an extension for Visual Studio Code, a popular code editor.

The technical details can get pretty deep, but here’s a bird’s-eye view of what’s involved:

1. Setting up the project: A developer starts by creating a new project in Visual Studio Code with the Microsoft 365 Agents Toolkit.

2. Configuring the AI: Next, they have to connect the project to an AI model, like one from OpenAI or Azure OpenAI, and plug in all the necessary API keys and credentials.

3. Building the logic and actions: Using the Agent Builder, they design the agent's workflow, spelling out what it can do and how it should reply to different questions.

4. Connecting to Teams: The agent is then linked to Microsoft Teams through the Connector Registry. This is what allows it to read messages and post replies in specific channels or chats.

5. Deployment: Finally, the developer has to push the agent to a cloud service so it can be online and available 24/7.

This video introduces the Microsoft 365 Agent SDK, a developer-focused toolkit for building advanced copilots.

The main thing to understand here is that this is a technical, multi-step process from start to finish. It’s designed for software engineers, not for the support manager, IT lead, or HR partner who just wants to set up a simple internal helpdesk.

Potential use cases for Microsoft Teams integrations with AgentKit

If you have the technical firepower to build a custom agent, it can be pretty handy for specific, internal tasks. A custom-built agent can be fine-tuned to your company’s exact processes and data.

Here are a few common ideas:

• Internal IT helpdesk: An agent could hang out in an #it-support channel in Teams and answer common questions like "how do I reset my password?" or "how do I get access to the marketing folder?" It could even be programmed to create a ticket in a system like Jira Service Management if it gets stuck.

• HR policy questions: Instead of pinging the HR team, employees could ask an agent questions about the company handbook, vacation policies, or benefits. The agent would be trained only on internal HR documents to give accurate answers.

• Project management assistant: You could connect an agent to your project management tools to give quick status updates inside a project’s Teams channel. You could ask things like, "what’s left to do for the Q4 launch?" and get an instant summary.

The hidden work and limitations of AgentKit

AgentKit offers a ton of flexibility for developers, but that same flexibility creates some real roadblocks for businesses that just want a solution that works, and works fast. Before you dive in, it’s worth understanding the hidden complexities that come with a developer-first toolkit.

High demand for developer time

Building an agent with this toolkit isn't a one-and-done job. It requires dedicated developer hours to design, build, test, and deploy. And the work doesn't stop at launch. Anytime you want to tweak the agent's personality, add a new knowledge source, or teach it a new skill, you'll need a developer to go back into the code. This makes you dependent on your engineering team and can really slow things down.

For teams that need a smart AI solution without hiring a whole new AI squad, a platform like eesel AI offers a much simpler route. It’s a completely self-serve experience, so you can get up and running in minutes, not months. You can connect Microsoft Teams, train the AI on your company knowledge, and launch an agent without writing a single line of code.

A look at the self-serve customization and workflow screen in eesel AI, an alternative to developer-heavy Microsoft Teams integrations with AgentKit.

Unpredictable costs

AgentKit's pricing is tied directly to your OpenAI API usage. That means your bill is based on how many "tokens" (which are like pieces of words) your agent processes. This model is famously hard to predict. If you have a busy month and employees are asking the agent a lot of questions, you could get a surprisingly high bill. That makes it tough to budget for, especially as your company grows.

This is a common headache with developer-first tools. eesel AI solves this with clear and predictable pricing. Our plans are based on a set number of AI interactions each month, with no hidden fees, so your costs are always under control. You know exactly what you're paying, no matter how much you use it.

The clear and predictable pricing page for eesel AI, contrasting with the variable costs of Microsoft Teams integrations with AgentKit.

Manual AI training process

With AgentKit, the agent doesn't just absorb everything about your company. You have to manually build the entire knowledge pipeline, setting up each connection to your different data sources one by one. It doesn't automatically learn from your company's unique lingo or past conversations; a developer has to program all of that logic.

eesel AI is built to unify your knowledge from the start. It can automatically train on your existing knowledge bases, like Confluence pages, Google Docs, and even past support tickets to understand your company's specific context and tone of voice from day one. It does the heavy lifting, so your AI is smart and relevant right out of the gate.

An infographic showing how eesel AI unifies knowledge from various sources, simplifying the setup compared to manual Microsoft Teams integrations with AgentKit.

Significant testing and deployment challenges

This is a big one. How can you be sure your custom agent will work correctly before you unleash it on your employees? With a toolkit like AgentKit, testing often involves a lot of manual spot-checks and building complicated evaluation systems. It's easy for mistakes to slip through, and a glitchy agent can damage trust pretty quickly.

eesel AI offers a powerful simulation mode that lets you test your AI on thousands of your past conversations before it ever talks to a real person. You can see exactly how it would have answered, get an accurate forecast of its performance, and fine-tune its behavior. This lets you deploy with confidence, knowing it's ready for the real world.

The powerful simulation mode in eesel AI for testing Microsoft Teams integrations with AgentKit alternatives, ensuring reliable deployment.

Pricing for Microsoft Teams integrations with AgentKit

The total cost of running an AI agent in Teams has a few different parts. You've got the cost of the platform itself (Microsoft Teams) and the cost of the AI that powers the agent (which, with AgentKit, is the OpenAI API).

Microsoft Teams pricing

Microsoft Teams is usually bundled into a Microsoft 365 subscription. For businesses, the pricing is pretty straightforward and based on a per-user, per-month fee. Here are the common plans:

You can always find the latest plans and features on the official Microsoft Teams page.

OpenAI AgentKit pricing

This is where it gets a bit fuzzy. AgentKit itself doesn't have a price tag. Instead, your costs are based on the API usage of the OpenAI models powering it, like GPT-4o. This is a "pay-as-you-go" model based on tokens.

Basically, every question an employee asks and every answer the agent gives uses up tokens, and you get a bill for the total number used each month. This makes your costs variable and highly dependent on usage. On top of that, you might have other costs for using certain tools or storing data. This model makes it very hard for businesses to budget accurately compared to a solution with a fixed monthly cost.

The verdict: Are Microsoft Teams integrations with AgentKit right for you?

When you look at the whole picture, it’s clear that AgentKit is a great choice for a very specific kind of company: a large tech firm with a dedicated AI engineering team that needs complete, granular control over every tiny aspect of their agent. If you have those resources and the need to build a totally custom AI from the ground up, it’s a fantastic toolkit.

But for most businesses, especially teams in support, IT, and HR, AgentKit probably isn't the right tool for the job. The deep technical requirements, the constant need for developer resources, and the unpredictable costs make it an impractical and expensive option. These teams don't need a complex toolkit; they need a solution that’s built to solve their problems, plain and simple. They need a tool that’s easy to use, delivers value quickly, and has a predictable return on investment.

A better alternative for Microsoft Teams integrations with AgentKit

Instead of wrestling with complicated toolkits, there’s a solution designed from the start to bring powerful AI into your business without all the headaches. eesel AI offers a completely different approach.

Here’s why it’s the better way for most businesses:

• Radically simple and self-serve: You don't need a developer. You can connect your knowledge sources, set up your agent, and launch in Microsoft Teams in a matter of minutes, not months.

• Total control without code: A simple, intuitive interface gives you full control over what the AI automates, its personality, and the specific actions it can take. No coding needed.

• Unified knowledge: eesel AI instantly learns from all your sources, internal wikis, documents, and even past conversations, to provide answers that are accurate and aware of your company’s context.

• Risk-free deployment: Our simulation mode lets you test your agent on your own historical data, so you can roll it out with total confidence.

• Transparent pricing: No surprise bills at the end of the month. Just straightforward monthly or annual plans that are easy to budget for.

Ultimately, eesel AI isn't just an alternative; it's the purpose-built solution for bringing powerful, reliable, and easy-to-manage AI into your Microsoft Teams workspace.

Try eesel AI for Microsoft Teams for Free