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Codewalk
Dependency-aware AI for code review and code understanding
Large codebases are hard to review and even harder to understand. Codewalk grounds AI in your repository instead of guessing. AI code reviews work instantly on PRs—no indexing required. For deeper understanding, Codewalk builds a dependency graph and semantic index to answer questions with source-cited code and visualize blast radius before you refactor. Open source, self-hosted, and available as an MCP server, web app, or API.
I built Codewalk because I was frustrated with AI code review tools that only look at a diff. They don't understand your codebase, so they miss architectural impact, hidden dependencies, and often produce generic feedback.
Codewalk takes a different approach.
For code reviews, there's no repository indexing required. Just point it at a PR or diff, and it analyzes dependency impact, architectural risks, blast radius, and import cycles.
For repository understanding, Codewalk builds a dependency graph and semantic index, giving AI the context it needs to answer questions with source citations and help you navigate unfamiliar codebases.
It supports three core workflows:
🔍 Dependency-aware code reviews with blast radius, architectural risk, and import cycle detection
💬 Repository Q&A grounded in your code with source citations
🛠️ Code understanding & refactoring, showing what changes are affected before you modify them
You can run Codewalk as:
🖥️ An MCP server for Claude Code, GitHub Copilot, and other MCP clients
⚙️ A self-hosted API for CI and automation
🌐 A web app with a repository knowledge graph explorer
It's open source, self-hosted, and supports multiple languages through Tree-sitter.
The idea came from repeatedly inheriting unfamiliar codebases and wishing AI understood the architecture before giving advice instead of just reading changed lines.
I'd love your feedback:
Would you use it inside your IDE or in CI?
Which capability is most valuable: code review, repository understanding, or blast radius analysis?
What's missing before you'd trust it on your own repository?
Thanks for checking it out! Looking forward to hearing your thoughts.
Spun it up on a messy internal repo and the blast radius view actually made a gnarly refactor feel manageable. Love that it just works on PRs without waiting on an index.
About Codewalk on Product Hunt
“Dependency-aware AI for code review and code understanding”
Codewalk was submitted on Product Hunt and earned 4 upvotes and 3 comments, placing #138 on the daily leaderboard. Large codebases are hard to review and even harder to understand. Codewalk grounds AI in your repository instead of guessing. AI code reviews work instantly on PRs—no indexing required. For deeper understanding, Codewalk builds a dependency graph and semantic index to answer questions with source-cited code and visualize blast radius before you refactor. Open source, self-hosted, and available as an MCP server, web app, or API.
Codewalk was featured in Open Source (68.6k followers), Developer Tools (516.2k followers), Artificial Intelligence (474.1k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 223.9k products, making this a competitive space to launch in.
Who hunted Codewalk?
Codewalk was hunted by Aakash Gupta. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Codewalk stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Aakash Gupta
Hey Product Hunt! 👋
I built Codewalk because I was frustrated with AI code review tools that only look at a diff. They don't understand your codebase, so they miss architectural impact, hidden dependencies, and often produce generic feedback.
Codewalk takes a different approach.
For code reviews, there's no repository indexing required. Just point it at a PR or diff, and it analyzes dependency impact, architectural risks, blast radius, and import cycles.
For repository understanding, Codewalk builds a dependency graph and semantic index, giving AI the context it needs to answer questions with source citations and help you navigate unfamiliar codebases.
It supports three core workflows:
🔍 Dependency-aware code reviews with blast radius, architectural risk, and import cycle detection
💬 Repository Q&A grounded in your code with source citations
🛠️ Code understanding & refactoring, showing what changes are affected before you modify them
You can run Codewalk as:
🖥️ An MCP server for Claude Code, GitHub Copilot, and other MCP clients
⚙️ A self-hosted API for CI and automation
🌐 A web app with a repository knowledge graph explorer
It's open source, self-hosted, and supports multiple languages through Tree-sitter.
The idea came from repeatedly inheriting unfamiliar codebases and wishing AI understood the architecture before giving advice instead of just reading changed lines.
I'd love your feedback:
Would you use it inside your IDE or in CI?
Which capability is most valuable: code review, repository understanding, or blast radius analysis?
What's missing before you'd trust it on your own repository?
Thanks for checking it out! Looking forward to hearing your thoughts.