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Developer Tools AI Tools
Discover and compare the best developer tools AI tools and software. Browse 413+ curated tools with reviews and rankings.
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Crawler.sh is a fast, local-first web crawler and AEO & SEO analysis tool that runs from the terminal or desktop app. It crawls entire sites in seconds, runs automated SEO checks, and extracts content as clean Markdown.
Rank #1
One workspace built specifically for freelance creative professionals who run the whole project.
buildarc is a CLI tool that reads Claude Code session transcripts and turns them into content you can actually post. With one simple command, it processes your development sessions and generates ready-to-share content.
JSON Exporter/Importer is a Figma plugin that bridges the gap between design and development workflows. It allows designers to export design tokens to various code formats and developers to import tokens while preserving existing work.
BrightBean provides TikTok-winning hooks and video formats as structured context for AI agents. It helps generate viral content with proven insights by studying high-performing TikTok videos.
mdspec.dev is an open-source lightweight specification management platform for technical teams. It helps create, track, and collaborate on technical specifications.
IndieBar is a macOS menu bar app that displays Stripe revenue, RevenueCat subscriptions, and Google Analytics traffic at a glance. It provides instant sale notifications and tracks MRR, churn, trials, and live users across multiple projects.
Octrafic is an open-source CLI for API testing that lets you describe tests in plain English. It handles everything from generating requests to validating responses and exporting PDF reports.
Epismo Skills provides community-built best practices that AI agents can instantly adopt and execute with everyday tools. It enables users to find proven workflows, capture expertise, and operate workflows as ongoing projects.
WebSocket Mode for the Responses API maintains persistent connections for AI agents, sending only incremental inputs instead of full context. This reduces end-to-end latency by up to 40% on heavy tool-call workflows.