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WrightAI
Auto-generate docs that never go out of date
Wright AI generates, maintains, and serves your code documentation automatically. → AST-level parsing across Python, JS, TS, Java, Go, Rust → Drift detection — flags stale docs inline when code changes → MCP server — Claude Code, Cursor & Copilot can query your docs live → VS Code extension, CLI, GitHub Action — works wherever you work One command to start: pip install wright && wright init
WrightAI was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #28 on the daily leaderboard. Wright AI generates, maintains, and serves your code documentation automatically. → AST-level parsing across Python, JS, TS, Java, Go, Rust → Drift detection — flags stale docs inline when code changes → MCP server — Claude Code, Cursor & Copilot can query your docs live → VS Code extension, CLI, GitHub Action — works wherever you work One command to start: pip install wright && wright init
On the analytics side, WrightAI competes within Productivity, Developer Tools and Artificial Intelligence — topics that collectively have 1.6M followers on Product Hunt. The dashboard above tracks how WrightAI performed against the three products that launched closest to it on the same day.
Who hunted WrightAI?
WrightAI was hunted by Suraj Sahoo. 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.
For a complete overview of WrightAI including community comment highlights and product details, visit the product overview.
Suraj Sahoo
Hey PH!
Built this because I kept running into the same problem
on every team I've worked on — documentation that starts
honest and slowly becomes a liability.
The part I'm most excited about is the MCP server. For the
first time, the AI tools you already use — Claude Code,
Cursor, Copilot — can actually query your codebase docs
live instead of starting from zero every session.
Would love to hear from anyone who's dealt with the same
documentation rot problem. What's your current workflow?
Happy to answer any questions about how it works under the
hood.
Try it for free → Wright AI