Copilot Studio Agent resetting when processing PDF drawings (300MB+) via Claude 4.6 Sonnet
Hello everyone, I am building an automated drawing review verification agent inside Copilot Studio using the Claude 4.6 Sonnet model. The goal of the agent is to read a comments package (20-40MB) and verify if those design comments were successfully incorporated into a milestone drawing set (300MB–400MB). When testing this workflow natively within Claude, the model handles the token load perfectly and returns an accurate compliance/incorporation summary within approximately 20 minutes. However, when running the exact same agent setup within Copilot Studio, the conversational canvas repeatedly crashes and resets the session. I suspect I am hitting the 100-second synchronous conversational timeout or overloading the chat runtime payload limits due to the massive file sizes. Because of corporate compliance policies, this agent must live within our Microsoft tenant so it can be scaled across our operations team via Microsoft 365. How can I fix Copilot Studio to have its performance match Claude's, as it is utilizing the same agent model. I am fairly new to working with AI but am willing explore any avenue as if I can figure out a solution this will help save a lot of time for colleagues. Thanks in advance for any insights!
Copilot studio Agent Dataverse index issues.
We are testing a Copilot Studio agent and would like to test/use Dataverse as a data source. At a very basic level, the Dataverse table has been created with the following columns: Category Question and topic Answer to customer The challenge is that our Copilot Studio agent cannot find any relevant answers or data from our Dataverse table. Under ‘Knowledge’, our Dataverse table shows a status of: ‘Unknown’. It has remained in this state for several days. Removing and re-adding the knowledge source does not help. What are we doing wrong?Platform Issue: Agent-Level MCP Initialization Blocks All Topics for Users Without Connection Access
I’m writing to report a significant platform behavior issue we’ve encountered with MCP (Model Context Protocol) server initialization in Copilot Studio that is severely impacting end-user experience. ENVIRONMENT • Platform: Microsoft Copilot Studio • Deployment Channel: Microsoft Teams • Agent Type: Custom Agent (EdiSENSE DEV) • MCP Server: Atlassian Confluence-Jira MCP • Affected Users: Users without Confluence/Jira access entitlements PROBLEM SUMMARY When an MCP server is registered at the agent level in Copilot Studio, it appears to be initialized globally before any topic routing occurs. If a user’s MCP connection is in a Not Connected state — even if their query has absolutely nothing to do with that MCP server - the agent gets stuck in an authentication loop, repeatedly prompting: “Let’s get you connected first. Open connection manager to verify your credentials. Once the connection is ready, retry your request.” The user is shown Retry / Cancel buttons, and the agent never proceeds to route the query to the appropriate topic. STEPS TO REPRODUCE 1. Register an MCP server (e.g., Confluence-Jira) at the agent level in Copilot Studio 2. Deploy the agent to Microsoft Teams 3. Log in as a user who does NOT have access to the MCP-connected service (e.g., no Confluence license) 4. Ask the agent any question completely unrelated to the MCP service 5. Observe: Agent does not route to any topic. Instead, it loops on MCP connection prompt indefinitely EXPECTED BEHAVIOR • MCP initialization failure for a specific service should NOT block unrelated topic routing • The agent should gracefully degrade - if an MCP connection is unavailable for a user, it should skip that MCP and continue routing the query to relevant topics • There should be a way to scope MCP connections to specific topics, or at minimum, mark them as optional/non-blocking ACTUAL BEHAVIOR • Agent-level MCP initialization blocks the entire conversation flow • Users without MCP access cannot use ANY functionality of the agent, even features completely unrelated to the MCP service • There is no graceful fallback or bypass mechanism available to agent builders BUSINESS IMPACT This is a critical gap for enterprise deployments where: • Not all users have access to every integrated service • Agents serve a broad user base with varying entitlements • Admins have no control over MCP initialization order or failure handling In our case, a large portion of our Teams users are completely locked out of the agent’s core functionality simply because they don’t have a Confluence license - even though they never intended to use Confluence-related features. FEATURE REQUEST / SUGGESTED RESOLUTION 1. Allow MCP servers to be scoped at the topic level, not just agent level 2. Introduce an optional flag for MCP connections so initialization failure is non-blocking 3. Provide agent builders with a connection status condition node in the topic flow to handle MCP failures gracefully 4. At minimum, allow the Cancel button in the auth prompt to fall through to normal topic routing I’d appreciate any guidance on whether there is a current workaround, or if this is a known limitation on the roadmap for resolution. Thank you for your time and support.
How to use agents response as an input to a topic?
Hi I would like to use the agents reponse to store it in a word or excel file. For that, I would like to use the response provided by the agent, pass it on to my custom topic which triggers an agentic workflow to store the agents response in a word or excel file. I cannot sort out how to pick the agents response and pass it on to my custom topic, any help will be highly appreciated, thanks!
Copilot Studio + SharePoint: Markdown (.md) Files in Doc Libraries Supported as Knowledge Sources?
Hi all, We’ve been doing some deeper testing with Copilot Studio agents grounded in SharePoint knowledge sources, and I’m hoping to clarify whether what we’re seeing is a known limitation or an undocumented gap. Scenario A Copilot Studio agent uses SharePoint document libraries as a knowledge source The library contains Markdown (.md) files that are intentionally used as canonical design references The same .md files: ✅ Work well when uploaded directly to the agent ❌ Are not retrievable or citable when stored in a SharePoint library and added as a SharePoint knowledge source To help with grounding, we created modern SharePoint index pages that: Explain what the markdown collections are (Patterns, ADRs, Guardrails) Link directly to the canonical folders and files Explicitly state that the .md files are the source of truth The agent can: Discover and summarize the index pages correctly Understand that .md artifacts exist and where they live But it cannot: Read the content of the individual .md files Apply a specific pattern or ADR from those files in a design conversation Cite them as sources, even when permissions and search indexing are confirmed What We’ve Checked Permissions (agent user has access) Folder depth (kept shallow) Search results (markdown files appear in SharePoint search) SharePoint indexing status Work IQ enabled Same content works when attached directly to the agent This behavior also seems consistent with what others have reported here: Markdown works when uploaded directly Markdown retrieval degrades when hosted in SharePoint libraries Questions for the Product Team / Community Are Markdown (.md) files in SharePoint document libraries officially supported as Copilot Studio knowledge sources today? If yes, are there specific constraints (file size, rendering, parsing, indexing) that differ from Word/PDF? If no (or “not yet”), is this a known limitation on the roadmap? Is the recommended pattern to: Convert important markdown files into .aspx pages, or Use thin “index / summary” pages and keep markdown canonical until retrieval improves? We’re happy to adapt our information architecture — just trying to align with the intended platform direction rather than work against it. Thanks in advance for any guidance or clarification. This capability is extremely powerful, and clearer expectations here would help a lot of teams make the right design tradeoffs.
