How to Connect GitHub to ChatGPT (2 Steps, No Code)

The fastest way to connect GitHub to ChatGPT is to install Windsor’s native ChatGPT app and link your GitHub account through Windsor.ai, a two-step process that takes under a minute and needs no code.

Without it, engineering and DevOps teams tracking repository activity, issue backlogs, or contributor output are left pulling data from the GitHub API by hand or building custom scripts to get it into a spreadsheet. Connecting GitHub to Windsor.ai gives ChatGPT direct, live access to repository, issue, pull request, and contributor activity data, so you can ask questions about your codebase and team output in plain language instead of writing queries against the GitHub API.

2 steps to connect GitHub to ChatGPT

Takes under a minute, no code or manual API scripting required.

For the full walkthrough, see Windsor’s documentation on integrating data into ChatGPT.

Prerequisites

• A Windsor.ai account (free forever plan, no credit card, or a paid plan starting at $19/month)
• A GitHub account with at least one repository or organization you have access to
• A ChatGPT account that supports installing apps

Step 1. Connect GitHub to Windsor.ai

• Create a free account at onboard.windsor.ai/app/github
• Select GitHub from the list of data sources
• Authorize Windsor.ai to access your GitHub account or organization
• Connect additional repositories or organizations if you manage more than one

Step 2. Connect the Windsor.ai app in ChatGPT

In ChatGPT, open the apps menu and install Windsor’s native app, then approve the requested permissions.

Once installed, confirm the connection is live:

List the data sources connected to my Windsor account. Do you see GitHub there?

If GitHub shows up in the list, you’re ready to start asking ChatGPT about your repositories, issues, and contributors in plain language.

The metrics that matter for GitHub

Metric	What it tells you
Stars	How many people have starred a repository, a rough signal of external interest and adoption.
Forks	How many people have copied a repository to build on it or contribute back, a sign of active reuse beyond the original team.
Open Issues Count	The size of a repository’s current backlog of open issues and pull requests combined.
Issue State	Whether an individual issue is open or closed, the basis for tracking how fast a backlog gets worked down.
Issue Comments	How much discussion a single issue has generated, useful for spotting contentious or high-attention items.
Pull Request Merged At	When a pull request actually shipped, letting you separate real merged work from PRs that were simply closed.
Pull Request Additions	Lines of code added in a pull request, one input into how large or risky a change is.
Pull Request Deletions	Lines of code removed in a pull request, useful alongside additions for judging the true size of a change.
Pull Request Review Comments	How many review comments a pull request received, a proxy for how thoroughly it was scrutinized before merge.
Contributor Commit Total	Total commits attributed to a single contributor, the base number for ranking individual output.
Review State	Whether a code review was approved, requested changes, or just commented, the outcome of the review step.
Workflow Run Conclusion	Whether a CI run succeeded, failed, or was cancelled, a direct read on build health.

What to ask ChatGPT: prompt ideas

Repository activity

Rank my repositories by stars and forks so I can see which ones are gaining the most outside traction.

List every repository where the open issues count has grown over the last month.

Pull request and code review velocity

Show me pull requests merged this week along with their additions and deletions, so I can see the size of what shipped.

Find pull requests with a high number of review comments that still don't have an approved review, so I know what's stuck.

Issue tracking

List open issues sorted by comment count so I can see which ones are generating the most discussion.

The GitHub connection through Windsor.ai is read-only. ChatGPT can analyze repository, issue, pull request, and contributor data, but it can’t create issues, merge pull requests, or change repository settings on your behalf.

Other ways to connect GitHub to ChatGPT

Manual export

You can pull issue, pull request, and commit data out of GitHub through its API or the repository Insights tab and load it into ChatGPT as a file. It works, but it’s a static snapshot: every update means exporting and uploading again, and there’s no way to ask a follow-up question against fresh data without repeating the whole process.

Zapier or Make

Automation platforms like Zapier or Make can move GitHub events, such as new issues or pull requests, into other tools as they happen. It’s a still-maintained workflow for triggering actions elsewhere, but it doesn’t give ChatGPT a queryable view of your historical repository data the way a direct connection does.

Neither approach gives ChatGPT the same live, ask-anything view into your GitHub data as connecting directly through Windsor.ai.

Conclusion

Connecting GitHub to ChatGPT through Windsor.ai turns repository, issue, and contributor activity into something you can ask about directly, without exporting files or writing scripts against the GitHub API. With 748 fields available, it’s enough detail to track engineering output alongside every other data source your team already has connected.

🚀 Ready to connect GitHub to ChatGPT? Connect GitHub to Windsor.ai and start asking about your repositories today.