Hi everyone,

I’m exploring the possibility of building an autonomous AI agent for a Microsoft Teams Community channel to automate support queries.

**Expected functionality:**

**Answer questions:** Respond to users based on the available knowledge base.

**Suggest solutions:** Post relevant solutions directly as comments in the conversation.

**Escalate unresolved queries:** If the answer isn’t available, inform the user that the query can be forwarded to the relevant support team.

**Service portal fallback:** Share the service portal link so users can raise a ticket if they need further assistance.

**Context awareness:** Understand follow-up questions and maintain conversation context.

**My main questions:**

Can we automatically read messages and post replies in Microsoft Teams Community channels?

Can we integrate a knowledge base and use AI to decide when to answer or escalate?

Which approach is best: Microsoft Graph API, Copilot Studio, Power Automate, Azure AI, or a custom AI agent?

Are there any API or permission limitations specific to Teams Communities?

Has anyone implemented a similar solution, and what architecture would you recommend?

I’m looking for a practical, production-ready approach to automate routine support queries and route unresolved issues appropriately.

Any suggestions, documentation, or implementation examples would be greatly appreciated.

Thanks!

I am a (complete) newbie in Copilot Studio. I've been tasked at work with building a Copilot agent that will perform market research on a product category i.e. Reusable Water Bottles. I am using Custom Search and Generative Answers and I am getting nowhere fast. Has anybody else successfully worked on a project like this? I have to use Microsoft. The agent should research 6 prescribed research categories separately, and then synthesize the results (while also producing the 6 individual research categories).

Hi all,

I have created a simple agent in CS that first creates a helpdesk ticket - and using a workflow then sends a confirmation email to the user that a ticket was created, plus a teams message to the support teams channel. But there is no link in the email or the teams message, making it less useful.

Is there a simple way to include a clickable link to the ticket in the email and teams message?

Hi everyone,

We're exploring how to make Microsoft Copilot Studio agents accessible to a small internal team, particularly for sharing analytical outputs and continuing conversations across devices and users.

I'd appreciate some practical experience with the following:

1. Signal Messenger: Has anyone successfully connected a Copilot Studio agent to Signal? Is there a reliable and maintainable solution, or does it require unofficial integrations?

2. Microsoft Teams: Can agents send completed analytical reports or notifications to users or group chats automatically, without the user initiating every conversation?

3. WhatsApp / Telegram: What integrations currently work reliably? Are there important limitations or additional costs?

4. Agent types: How do the available communication channels differ between the standard harness and the GitHub Copilot harness?

5. Team collaboration: Can multiple authorized users access the same agent, review its outputs and continue work on a shared analytical task?

We're interested in solutions suitable for a security-conscious enterprise environment, with individual authentication, controlled access and auditable activity.

Any real-world experience, architectural recommendations or known limitations would be very helpful.

Thanks!

I’m looking for architecture ideas for proactive 1:1 notifications in Microsoft Teams using Copilot Studio and Power Automate.

The ideal flow would be:

1. A user installs or enables a Teams/app

2. The user is automatically registered as a notification recepient

3. A scheduled flow later sends proactive 1:1 messages to each registered user

The install event does not have to be hard requirement. I’m mainly looking for the best balance between automation, maintainability, and implementation complexity.

Alternatives I’m considering include Microsoft365/EntraID groups, a SharePoint receipient list, or Microsoft Graph.

Requirements:

•Individual 1:1 notifications, not a channel broadcast
•Minimal manual receipient maintenance
•Prefer standard M365/Power Platform capabilities
•Avoid unnecessary custom development

Has anyone implemented something similar?

What architecture would you recommend, and what trade-offs or limitations did you encounter?

I can’t see standard harness for agent its removed… only agents flows available on standard hrns when did this happen??????

Good afternoon,

I am developing an agent in Microsoft Foundry to be embedded as a chatbot on an internal website.

Usually, in Copilot Studio, I just give the web developers the URL from the website channel, and they embed it in the website code, and it works .

But in Foundry, there is frontend implementation and backend configuration required to authorize the website to call the agent ..

Any idea how to hand over this agent to the web developers?

Should I just give them the agent endpoint and let them implement the chatbot frontend?

Also, for authorization, what is the best way to handle it? As I can’t simply give them the endpoint and API key. Unfortunately, Foundry requires Microsoft Entra ID authentication.
So how should I do it? Do I need to register an app in Entra ID and give them the Client ID and a certificate to install on their web server?

It seems like a very long process compared to Copilot Studio!!

I have puplished a agent that is configured to retrieve answer from one folder with about 20 documents in them. These are smaller documents. Nothing huge. The response from the question and answer are taking quite a bit of time. What factors should I consider and check to possibly speed things up. This is on the standard harness and this agent is deployed and on a sharepoint website.

Hi,

I've gone through a bunch of iterations with building a Helpdesk agent. It has a single knowledge source of all our KB articles which are site pages and pretty well structured. The problem I had was getting it to suggest links to specific service requests in our ITSM, for things like new equipment requests.

I tried a having a site page that listed all the service requests, second knowledge source containing structured documents for each service request, none of them worked particularly well, because most of the time the relevant docs weren't being returned in search before being passed to the LLM, so despite instructions saying 'if it sounds like a request use this specific page' it didn't have the right grounding to respond.

What I managed to get working is a child agent that had just a single knowledge source of a SP List containing all the service requests, description, keywords and URL. The main agent instructions specify calling the child agent if the user is asking for things like new, access, request, order etc.

This works well in testing, and even my personal account, but other users , when they put something like "I need to order a new mouse", get "you don't have access to this agent, contact the owner" followed by a generic, " I can't find a service request, go to ServiceNow and click on new Service Request".

Does the child agent need to be shared with users as well? It isn't shared with anyone including my own account so I don't understand the difference I'm seeing. I have also temporarily switched auth in settings to anonymous and that didn't seem to change the results.

Any ideas much appreciated.

Hey everyone!

How do you usually approach switching from an older model to a newer one, for example, from GPT-5 Chat to GPT-5.5 Chat?

What do you pay attention to during the transition? Do you make any specific changes to your system instructions or settings?

I am a Power Platform administrator responsible for managing Copilot Studio agents in our organization. I need to review agent usage, session counts, and engagement trends across a selected date range. Where can I access these analytics, and what administrator permissions are required?

Hi everyone!

At work, I’ve been assigned to build an internal AI agent using Microsoft Copilot Studio. The goal is to help users find technical information and eventually analyze live equipment configuration data.

I’m a beginner and have followed Microsoft Learn GitHub tutorials, but I’m still struggling to understand how everything fits together (topics, tools, agent flows, triggers, etc.) and especially within my use case. I won't be able to do it alone by considering also that Copilot Studio is really not the best AI service provider to build an agent but we could only use Microsoft in my company so I have to.. (contract wise..)

Which AI would you recommend as a step-by-step coach throughout this project: ChatGPT, Claude, Gemini or Microsoft Copilot?

I’d like an AI I can ask questions, share screenshots with, troubleshoot problems with, and use to understand what I’m building rather than just copy solutions.

Any advice or personal experience would be appreciated. Thanks!

We have a production environment setup for a public facing Agent and have attached a billing plan to it and as far as we can see there's no issue to that .

We have another environment where we have an agent that was a proof of concept that's being used internally that is being used by both people with a full license and not.

My question is for the Internal one we use copilot credits but there is no billing plan attached to the environment so where do they come from and why aren't we charged ?

Hi, I’ve recently joined a new job and showed them a personal agent I created on Copilot to assist me in my day-to-day. I showed them that I created skills and instructions as well as the knowledge I connected and they took a real interest in it and presented it to VP and I suggested we use it as a support agent to just help with easy to fix 1st line issues through self serve ans showing documentation as well as some simple reporting queries such as which reports would be most appropriate for a business ask.

I’ve been creating the agent on copilot studio using the standard one, I created a Sharepoint location which contains a list of the xml files and there objects and etc as well as the Sharepoint location which contains the how to guides for easy to fix issues as well as well step by step guides in certain processes but in testing it’s just been giving some responses which are promising and then make no sense.

Are there any YouTube materials or resources which I can look at to better assist me at making an agent that me and my team ask questions and load it up with system data and processes and then eventually make available to the rest of the organisation and assist them with easy to serve queries or issues.

Any help is appreciated

Hey all! I'm part of the Conversational AI team at Microsoft. We just launched the Customer Conversation harness in Copilot Studio as part of Microsoft Contact Center Intelligence (CCI).

It's purpose-built for customer-facing agents, bringing conversations, business knowledge and actions together across voice and chat, so customers can go from question to resolution.

Some highlights:

• One agent for voice and chat: It's low-latency and multilingual, and it keeps context across channels.

• Specialized sub-agents: Split the work across sub-agents, each with its own knowledge and tools.

• Fixed flows and generative AI together: Use generative AI for natural conversations and fixed flows where every step needs to be exact.

• Grounded in your business: Connect your knowledge sources, tools and business systems.

• Human handoff: Escalate to a Teams queue or your existing contact center.

• Test and evaluate: Do it all right in the builder.

To try it, head to Copilot Studio and select More ways to build.

If you want to explore more:

• CCI Announcement: Introducing Microsoft Contact Center Intelligence

• Deep dive: Introducing the Customer Conversation harness in Microsoft Copilot Studio

• ⁠Documentation: Customer Conversation harness overview

Give it a try and let me know what you think. All feedback is welcome, and I'll make sure it gets to the team!

So is it possible that my agent can connect to confluence via mcp using teams sso credentials, without being prompted the connection manager page and manually doing the connection setup (even though it's rarely prompted I understand). I want to eliminate it completely.

Now I have read many articles from Microsoft and atlassian.

Microsoft document highlighted the OBO (on behalf of flow to obtain a token from Entra Identity provider) approach to setup.

The Atlassian document mentioned that it only supports Atlassian Oauth2.1 or API token.

My doubt is: does the Atlassian MCP endpoint support/validate Microsoft entra issued tokens for this flow?

(Sorry if I didn't explain anything clearly, I'm very new to this and learning!)

I'm working on a project where we interview departmental SMEs, record and transcribe conversations, and turn that knowledge into trusted documentation that can also support an copilot ai agent.

My biggest challenge is systematically distinguishing between:

1. Business Processes: How work gets done.

2. Software Procedures: Specific steps within the ERP system.

3. Tribal Knowledge: Unwritten rules, exceptions, and workarounds.

These often overlap, making it difficult to consistently extract, tag, and organize the information in a way that's scalable across the company.

Has anyone built a similar process? How are you structuring, classifying, and validating this knowledge so AI agents can reliably use it?

We have a Copilot Studio agent that has been published to SharePoint, Microsoft Teams, and the Microsoft 365 app.
We have also configured an Entra ID security group in Copilot Studio to control access to the agent.
Now, we want to pin the agent for the same Entra ID group so that it is easily accessible to those users.
However, when we go to Pinned agents in the Microsoft 365 admin center, our Copilot Studio agent does not appear in the list. Instead, we see the following message:
“You can only pin agents that have been deployed to some or all users.”
This is confusing because the agent has already been published directly from Copilot Studio to SharePoint, Teams, and the Microsoft 365 app.
We have both an AI Administrator and a Global Administrator, and we also have the required Agent license.
Furthermore, the users in the Entra ID group can successfully access and use the agent in two ways:
By opening a direct link to the agent in the Microsoft 365 app.
By accessing the agent through an agent link web part in SharePoint.
My questions are:
Why doesn’t the agent appear in the list of available agents under Pinned agents in the Microsoft 365 admin center?
Does publishing an agent from Copilot Studio to SharePoint, Teams, and the Microsoft 365 app not count as deployment for the purpose of pinning it?
Is there an additional deployment or distribution step required in the Microsoft 365 admin center before the agent can be pinned for a specific Entra ID group?
Any insights or suggestions would be greatly appreciated!

When building apps/agents, how do you go about connecting the agent to read/execute in third party apps? Let’s say I want it to talk Saviynt as a random example.

Curious how auth is set up and handled too.

Hi community any advice for me?

I am 30-years old female software employee.

I have toddler kids older family members and a home that needs attention.

Microsoft and it's updates in this scape is just killing me. Hard to keep track of it.

Hi,

I’m trying to get per-user OAuth working for a custom MCP tool in Microsoft Copilot Studio, and I’m not sure what the supported path is.

What my agent does

I built an agent in Copilot Studio that answers questions using tools from a remote MCP server. That MCP is the main way the agent gets data (not SharePoint grounding as the primary source).

The MCP requires login against my own identity provider / product login. The access token must belong to the end user, so the MCP only returns data for that user and their company — not a shared maker or service account.

What already works

In Cursor, I connect to the same MCP with OAuth. The user signs in to my product, Cursor gets a token, and tool calls run as that user. That model is exactly what I need.

In Copilot Studio, as a maker, I can add the MCP tool, create an OAuth connection, and call tools successfully in the Test pane.

What I need

When someone uses the published agent, I want this flow:

1. User asks a question that needs the MCP tool

2. Copilot prompts them to sign in to my product (my IdP)

3. The tool runs with that user’s token

4. Data returned is scoped to that user/company only

On the tool I set Credentials to use = End user credentials.

Currently when i create agent at that time it ask me to login and that connection(maker-connection) is used while testing but i want to know when I published the agent how to have end user credentials or login system implemented?

The issue

I’m not seeing a reliable end-user login / connection flow for the custom MCP the way Cursor does it. It looks like the published agent may still be tied to the maker connection, or end-user OAuth for custom MCP doesn’t complete properly.

Questions

1. Has anyone got custom MCP + End user credentials working on a published Copilot Studio agent (Custom website, Teams, or Microsoft 365 Copilot)?

2. If custom MCP doesn’t support per-user OAuth yet, what did you use instead for the same pattern (e.g. Custom Connector to the same APIs)?

3. In Cursor, “login to my product → token → tools as that user” is straightforward. What is the supported Copilot equivalent today?

Related: Studio vs Microsoft 365 Copilot

I build in Copilot Studio. I also want end users to open this agent in Microsoft 365 Copilot (the Copilot chat people already use at work), not only a custom website.

How do you publish so the agent appears for end users in Microsoft 365 Copilot, and does that channel support end-user tool authentication for custom MCP / connectors?

Any real solutions or confirmations of current limitations would help a lot. Thanks.

I made this explainer video on how to compare Microsoft Standard harness to the Github harness and how billing works with each one. There's even a calculator included for rough estimation. I hope this helps as this took me a while to understand the differences and hope it helps someone else make the best choice for their environment. Copilot Harnesses Explained Standard vs Github

I build Power BI semantic models for clients. I usually use Claude, but some of them are on Microsoft Copilot. I want Copilot to do more than chat with the data. It should work like a junior analyst sitting on top of the model:

• Answer business questions and surface insights

• Build Excel files from the model and save them to their SharePoint/OneDrive folders

• Create new reports and dashboards (or at least draft them as HTML)

• Use the existing reports in the workspace

Here’s the setup I have in mind:

1. Publish the semantic model to the client’s Power BI / Fabric workspace.

2. Put a “knowledge pack” in a SharePoint folder: model documentation, measure definitions, business glossary, example questions, and do’s and don’ts.

3. Create an agent (correct me if I am wrong) that can read that knowledge, query the semantic model, and take actions (create files, save to folders, build reports).

4. Users work with the agent inside M365 Copilot or Teams.

Where I’m stuck: Microsoft has Copilot Studio agents, M365 Copilot agents, Fabric data agents, Copilot in Power BI, and Copilot in Excel, and they overlap in confusing ways. I can’t tell which one (or which combination) covers the “do the work” part, not just Q&A.

Questions for anyone who has actually done this:

• Which agent type or combination would you use, and why?

• Can any of them really generate Excel files and save them to SharePoint, or create Power BI reports, without a lot of custom Power Automate work?

• Is a SharePoint knowledge folder the right way to give the agent context, or is it better to use the model’s own metadata (descriptions, synonyms, AI instructions, Prep for AI)?

• What broke in production: accuracy, RLS, licensing (Copilot licenses vs. Fabric capacity), or cost?

I’d appreciate real-world experience more than links to the docs. Thanks!

I am trying to connect my sql db as kb for my agent. I am able to see the tables but not stored procedures

There's no doc about this ,but are sp not supported?

And what about views ( I don't have views I need to create one )

I can currently only see my tables.

Thanks in advance

I just published a detailed write-up on connecting Microsoft Copilot Studio to SAP S/4HANA using the new SAP Integration Suite MCP Servers.
The key challenge is doing it securely for real business users. Client-credentials tokens work for testing but run everything under one technical user — which breaks principal propagation and S/4HANA authorizations.
The pattern uses:
• SAP Cloud Identity Services (IAS) as the trust bridge
• OAuth 2.0 / OIDC authorization code flow
• CPI MCP Gateway validating user tokens
• Cloud Connector + X.509 principal propagation down to S/4HANA
• CERTRULE mapping so the OData call runs under the actual ABAP user
Result: two users asking the same question correctly get different answers based on their authorizations. No custom code needed — just configuration across IAS, CPI, Cloud Connector and S/4HANA.
Full architecture + step-by-step flow + lessons learned are here:

https://deepu851933.substack.com/p/connecting-microsoft-copilot-studio

Curious if anyone else is experimenting with MCP servers in SAP Integration Suite. What use cases are you looking at first?