SonarQube

Open-source browser infrastructure for AI agents at scale

Steel is an open-source browser API purpose-built for AI agents, providing managed headless browser sessions with anti-bot bypass, proxy rotation, CAPTCHA solving, and session persistence. It handles the infrastructure layer that browser automation agents like Browser Use and Stagehand run on top of. Self-hostable or available as a cloud service. Over 6,000 GitHub stars.

Open-source background jobs and AI workflows for TypeScript

Trigger.dev is an open-source platform for building and deploying background jobs, AI agents, and long-running workflows in TypeScript. It eliminates serverless timeouts with durable task execution, automatic retries, queue-based concurrency control, and elastic scaling. Used by 30,000+ developers at companies like MagicSchool and Icon.com, it processes hundreds of millions of agent runs monthly. Backed by a $16M Series A led by Dalton Caldwell's Standard Capital fund.

Open-source PaaS alternative to Vercel, Heroku, and Netlify

Dokploy is a free open-source platform-as-a-service for self-hosting applications without cloud vendor lock-in. It provides automated deployments from Git repositories, built-in SSL certificates, database provisioning, Docker and Docker Compose support, and a clean web dashboard for managing multiple applications on your own servers. With 18,000+ GitHub stars, it fills the gap for teams wanting Vercel-like deployment simplicity on their own infrastructure.

Automated code review for any linter on CI

reviewdog is an open-source automated code review tool that integrates any linter or static analysis tool with GitHub, GitLab, Bitbucket, and Gitea pull requests. Parses output in errorformat, Checkstyle XML, SARIF, and JSON formats to post inline review comments on changed lines only. Works with GitHub Actions, Travis CI, CircleCI, GitLab CI, and Jenkins. Supports 40+ languages through universal linter adapter architecture.

xAI's terminal coding agent with parallel subagents and worktree-aware automation

Grok Build is xAI's terminal-first coding agent for planning, editing, testing, and reviewing code from a local CLI. The early beta exposes subagent controls, worktree mode, headless JSON output, best-of-N parallel attempts, sandbox profiles, and experimental memory. It fits developers comparing Claude Code, Codex, and Gemini CLI for local agentic workflows with deeper parallel execution.

Anthropic's agentic coding CLI

Anthropic's agentic CLI coding tool that delegates complex tasks to Claude directly from the terminal. Understands entire codebases via automatic context gathering, edits multiple files, runs shell commands, and manages Git workflows autonomously. Supports CLAUDE.md for persistent project instructions, integrates with VS Code and JetBrains, and uses Claude Opus/Sonnet with extended thinking for complex architectural decisions. Built for terminal-first developers.

The AI-first code editor

AI-first code editor built as a VS Code fork that deeply integrates LLMs into every part of the development workflow. Features Tab autocomplete with multi-line predictions, Cmd+K inline editing, AI chat with full codebase awareness, and Agent mode for autonomous multi-file edits with terminal execution. Supports GPT-4, Claude, and more with automatic context from project files and docs. Includes privacy mode for SOC 2 compliance. The leading AI-native IDE with 100K+ paying users.

OpenAI coding agent for app, editor, terminal, and cloud work

Codex is OpenAI's coding agent for software development across the Codex app, editor, terminal, and cloud tasks. It helps write, review, debug, refactor, and automate code, with ChatGPT plan access for managed surfaces and API-key usage for CLI, SDK, and IDE workflows. The open-source CLI and SDK support local repository work, while cloud features add GitHub review, Slack/Linear integrations, worktrees, skills, MCP, and automations.

Heterogeneous CPU-GPU inference and SFT for large MoE models

Open-source framework for running and fine-tuning large Mixture-of-Experts models with heterogeneous CPU-GPU execution, optimized kernels, limited VRAM and SGLang or LLaMA-Factory integrations.

Official Kubernetes and Helm reference stack built on the vLLM inference engine

Official vLLM reference implementation for scaling the existing inference engine on Kubernetes with Helm, request routing, KV-cache offload, autoscaling and Prometheus/Grafana observability.