Copilot Not Accessing Repos? Fixes, Security & MCP Explained

8/11/2025

Uh Oh, Copilot's Giving You the Silent Treatment? Here's Why It Might Not Be Accessing Your Repos & What's Up with MCP

Hey everyone, so you're trying to get your AI pair programmer, GitHub Copilot, to work its magic, but it's just... not. It feels like it's completely ignoring your own code, refusing to give suggestions based on your private repositories, or maybe it's just throwing up errors. It's a frustrating spot to be in, especially when you're on a deadline.

Let's talk about what's REALLY going on when GitHub Copilot can't seem to access your repos. We'll get into the common culprits, but I also want to dive into a much bigger, wilder story about Copilot's access that was making headlines. & you might've seen the acronym "MCP" floating around & are wondering if it's the bad guy here. We'll clear that up too.

Honestly, it's a bit of a complicated topic, so let's break it down.

The Simple Stuff First: Everyday Reasons Copilot Is on the Fritz

Before we get into the heavy stuff, let's cover the usual suspects. Most of the time, when Copilot is acting up, it's one of these common issues.

Authentication & Connection Errors: This is the number one cause. You might see an error like "GitHub Copilot could not connect to server." This usually means there's a hiccup with your GitHub account's connection. The first thing to try? The classic "turn it off & on again." Seriously. Log out of your GitHub account within your IDE (like VS Code), & then log back in. This often forces a refresh of the authentication token & gets things working again.
You Don't Have an Active Subscription: Copilot isn't free. If your trial has ended or your subscription has lapsed, it'll stop working. Double-check that you have an active Copilot plan associated with the GitHub account you're logged in with.
Network & Firewall Issues: Are you behind a corporate firewall or a particularly strict VPN? Sometimes, these can block the connection to GitHub's servers that Copilot needs to function. Your IDE needs to be able to talk to
1api.github.com
for Copilot to work. If you suspect this is the problem, you might need to talk to your IT department or check your firewall settings to allow traffic to GitHub.
Content Exclusions are Doing Their Job: This is a feature, not a bug! If you're working in a company, your organization's owner or the repository's administrator can set up "content exclusions." This tells Copilot, "Hey, don't touch the code in this file or these specific files." It's a way to prevent sensitive information like API keys or internal logic from being processed by the AI. So if Copilot is working in some files but not others, this could be why. It's actually a good thing for security.
IDE or Extension Conflicts: Sometimes, other extensions you have installed in your IDE can interfere with Copilot. Try disabling other extensions one by one to see if one of them is causing the conflict. Also, make sure your IDE & the GitHub Copilot extension itself are updated to the latest versions.

The Elephant in the Room: The "Zombie Repository" Nightmare

Okay, so we've covered the simple fixes. But there's a much bigger, more concerning conversation to be had about Copilot & repository access. For a while, the problem wasn't that Copilot couldn't access repos, but that it was accessing repos it absolutely shouldn't have been.

Turns out, a security firm called Lasso discovered a massive issue back in 2024. Microsoft's own Copilot was found to be leaking data from over 20,000 private GitHub repositories. These weren't just random projects; they belonged to giants like Google, IBM, PayPal, & even Microsoft itself. We're talking sensitive credentials, proprietary code, security tokens—the whole nine yards.

So, how did this even happen? The root cause was pretty shocking: it was all about caching.

Here's the breakdown:

A repository was public on GitHub, even for a short time.
Microsoft's Bing search engine indexed the content of that public repository.
The owner of the repository then made it private.
Here’s the kicker: Bing's cache never cleared that indexed data.
Since Copilot uses Bing's search index to inform its suggestions, it would pull from this cached, now-private data.

Lasso's team called these "zombie repositories"—code that was supposed to be private & dead to the public world but was still walking around in Copilot's brain. They even discovered one of their own private repos being exposed this way.

Microsoft tried to put a patch on it by blocking public access to Bing's cached data, but for a while, the fix was only skin deep. The data remained accessible to Copilot even when it was hidden from human users. This whole situation highlighted some serious questions about data privacy in the age of AI, especially when the same company (Microsoft) owns the code repository (GitHub), the search index (Bing), & the AI tool (Copilot).

This is a fundamentally different kind of "access issue." It’s not about a bug preventing you from using the tool; it’s about a deep, systemic flaw that exposed sensitive information. It’s a HUGE deal & something every developer should be aware of.

So, What on Earth is MCP & Is It to Blame?

Now, let's talk about MCP. You might have seen this acronym in GitHub's documentation or in discussions about new Copilot features & wondered if it's related to these access issues.

The short answer is: NO, MCP is not the cause of these problems. In fact, it's designed to do the opposite.

MCP stands for Model Context Protocol. It's an open standard that is all about extending the capabilities of GitHub Copilot in a controlled & transparent way. Think of it as a bridge that allows Copilot to connect to other tools, services, & data sources.

Here’s the thing: by default, Copilot's "context" is pretty much the code you have open in your editor & some general knowledge from its training data. MCP allows you to give it more context. You can hook it up to other systems.

For example, you could use an MCP server to:

Give Copilot access to your company's internal documentation or coding standards.
Connect it to a specific API so it can generate code that uses that API correctly.
Allow it to perform tasks on GitHub directly from your IDE, like creating an issue or reviewing a pull request.
Hook it up to your local development environment to run tests or compare branches.

So, far from being a rogue protocol causing access problems, MCP is a tool for developers to intentionally & securely give Copilot more power. It's about defining clear channels for the AI to get information, not about it randomly scraping data it shouldn't have. It puts you in the driver's seat, letting you decide what extra tools & knowledge you want your AI assistant to have.

This is where a tool like Arsturn comes into the picture, conceptually. While not directly using MCP, Arsturn operates on a similar principle of controlled data access for AI. When businesses want to deploy an AI chatbot for customer service, they don't want it pulling random information from the web. They want it to use their specific knowledge base, product info, & support documents. Arsturn helps businesses create custom AI chatbots trained on their own data. This ensures the chatbot provides accurate, instant support & engages with website visitors 24/7 using only the information it’s supposed to have. It's all about providing a personalized & controlled AI experience, which is the same philosophy behind MCP.

Tying It All Together: Your Access Problem vs. THE Access Problem

So, let's bring it all home. When you're troubleshooting why GitHub Copilot isn't working with your repository, you're most likely dealing with one of the "simple" issues: authentication, network problems, or a content exclusion setting. These are usually fixable with a bit of tinkering.

The bigger, more alarming "access problem" was the "zombie repository" issue, which was a data privacy failure, not a user-facing bug. This issue made it clear how important it is for AI systems to handle data responsibly.

& MCP? It's not the villain here. It's actually part of the solution for a more powerful & controlled AI future. It's a feature that allows developers & organizations to expand what Copilot can do by giving it explicit, permissioned access to more tools & data. It's a move toward making AI assistants more integrated into our specific workflows, not less secure.

For businesses looking to leverage AI on their own turf, the principle of controlled data access is paramount. When thinking about lead generation or customer engagement on your website, you want an AI that's an expert on your business. This is where a no-code conversational AI platform like Arsturn becomes so valuable. It lets you build an AI chatbot trained on your company’s data, ensuring it can have meaningful, personalized conversations that boost conversions, without the risk of it sharing incorrect or external information.

Hope this was helpful & cleared up some of the confusion around Copilot & its access to your code. It's a powerful tool, but like any technology, it's got its complexities & its cautionary tales. Let me know what you think