How to Give ChatGPT Access to a GitHub Repo

ChatGPT can connect to GitHub repositories through a built-in GitHub connector, letting it read code files, summarize pull requests, explain commit history, and assist with development tasks directly from the repo. Tools like fenbs keep the repository decisions, task scope, and handoff notes that should be shared across AI apps, so work that starts in ChatGPT can continue in Claude Code or another tool without losing context.

This guide explains how to connect ChatGPT to a GitHub repo, what it can read and write, how to manage the access safely, and how to share repository context across multiple AI tools.

How to connect ChatGPT to GitHub

In ChatGPT, open the connected apps or tools settings and look for GitHub. When you connect it, GitHub takes you through an OAuth authorization where you select which repositories to grant access to. You can grant access to all repositories or to specific ones only.

Once connected, you can ask ChatGPT to read files from the repository, summarize a pull request, explain a piece of code, or look up recent commits. The connection persists between conversations, so you do not need to reconnect each time. Check OpenAI's current documentation for which plans include the GitHub connector.

What ChatGPT can read in a repo

ChatGPT can read source code files, README files, configuration files, documentation, and commit history within the repositories you authorized. It can list files in a directory, read a specific file by path, and explain what the code does. This is useful for code review, understanding an unfamiliar codebase, and generating documentation.

For tasks that need ChatGPT to write and run code directly in the repository, see ChatGPT Codex, which provides a more direct coding agent workflow. The standard GitHub connector is primarily a reading and assistance tool rather than a coding agent.

File types such as images, compiled binaries, and large data files may not be readable in the same way as text-based source files. Focus ChatGPT on the text files relevant to your task for the most reliable results.

Write access and what it allows

Depending on the OAuth scope you grant, ChatGPT may be able to create branches, open pull requests, comment on issues, or push commits. Write access is more powerful than read access and should be granted only after careful thought.

If your goal is code review, documentation, or answering questions about the codebase, grant read-only access during the authorization step. Write access is appropriate when you have a clear workflow for reviewing every change ChatGPT proposes before it reaches a shared branch.

Never grant write access to a production branch without a human review step in place. ChatGPT can produce code that compiles and appears correct but introduces subtle bugs or security issues. A pull request workflow with a required human reviewer is the safer pattern.

Controlling which repos ChatGPT can access

During the GitHub OAuth authorization, you choose whether to grant access to all repositories or specific ones. Select specific repositories unless you have a clear reason to share everything. A focused scope limits what ChatGPT can reach if the connection is misused or if it misunderstands a request.

Review the list of authorized repositories periodically in your GitHub settings under Applications, then Authorized OAuth Apps. If you no longer use ChatGPT with a particular repository, remove it from the access list rather than leaving an open connection.

Using ChatGPT alongside other AI coding tools

Many development teams use more than one AI tool on a codebase. ChatGPT might handle code review and documentation, Claude Code might write new features, and GitHub Copilot might assist with autocomplete. Each tool starts a session without knowledge of what the others have done.

Recording architecture decisions, naming conventions, and current task scope in fenbs gives all connected assistants the same starting point. A decision made in a ChatGPT session such as moving from REST to GraphQL is available to Claude Code in its next session without anyone repeating it.

This matters most for decisions that affect multiple files or multiple sessions. A short task completed in one sitting rarely needs a shared record. A refactor that spans a week and involves different people and tools benefits from one agreed source of truth. Code conventions, dependency choices, and the components that should not be changed are the decisions most worth recording, because every session that touches the codebase needs them.

How to do this with fenbs

1. Create a free account. Your personal board is free and needs no credit card.
2. Add a project for the repository. Write a short description of the codebase, its current goals, and its main constraints.
3. Add tasks for the features, bugs, or refactors in progress. Note the task scope, which files are affected, and any restrictions.
4. Record architecture and code style decisions in Decisions and rules so every connected AI app reads them before starting work.
5. Connect ChatGPT and Claude Code over MCP from Integrations so both tools work from the same project context.

fenbs does not connect to GitHub directly. It keeps the project decisions and task context that make AI tools more effective when they work on the same codebase across sessions and across tools.