Select the exact parts of a repository and compile them into one clean text file for ChatGPT and Claude or Gemini. MashuPack is built for browser-based AI workflows where file-count limits, upload friction, and messy context assembly keep getting in the way. It makes code context portable, intentional, and easy to control.
I built MashuPack because I had a split workflow. In the terminal, I already had good tools for navigating codebases and working with agents in real time. But I still do a lot of long-form planning, debugging, review, and codebase understanding in conversational web UIs like ChatGPT and Claude.
That workflow kept breaking on context. File-count limits, upload limits, and inconsistent format support made it annoying to get the right slice of a codebase into the model. The one format that always seemed to work was a single text file.
So I started manually packing up small collections of source files whenever I wanted to discuss a subsystem, plan a refactor, or ask high-level questions about a repository. That got repetitive fast.
MashuPack came from wanting a better interface for that exact job: select the context you actually want, compile it into one clean file, and stay in control of what gets included.
I’d especially love feedback from people who use ChatGPT or Claude in the browser for software planning, debugging, or understanding unfamiliar codebases.
nice and simple utility, I've been using tree for this, but Mashupack is a nice visual way to solve the same problem.
This solves a very real Claude/ChatGPT workflow pain. Simple idea, high utility = dangerous combo 🔥
Do you keep file paths and a table of contents so the model can still reference where things came from?
A context manifest would be valuable here. Something like file list, timestamp, ignored paths, token estimate, and exclusions. That gives teams a lightweight audit trail for what was sent into ChatGPT or Claude.
About MashuPack on Product Hunt
“Turn codebases into a clean file for Claude and ChatGPT”
MashuPack launched on Product Hunt on May 25th, 2026 and earned 100 upvotes and 7 comments, placing #13 on the daily leaderboard. Select the exact parts of a repository and compile them into one clean text file for ChatGPT and Claude or Gemini. MashuPack is built for browser-based AI workflows where file-count limits, upload friction, and messy context assembly keep getting in the way. It makes code context portable, intentional, and easy to control.
MashuPack was featured in Productivity (652.4k followers), Developer Tools (513k followers) and Artificial Intelligence (469.4k followers) on Product Hunt. Together, these topics include over 300.2k products, making this a competitive space to launch in.
Who hunted MashuPack?
MashuPack was hunted by Spencer Nunamaker. 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.
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Spencer Nunamaker