# open-source

AI agent dev environment with parallel git worktrees, magic git commands, and Linear integration.

Jean is an open-source desktop dev environment for AI agents from coolLabs (the team behind Coolify). It runs multiple coding agents — Claude Code, Codex, and others — in parallel inside isolated git worktrees, each with its own chat session and terminal. Magic git commands handle commits, PR descriptions, code reviews, and merge conflicts with AI assistance, while built-in Linear and GitHub integrations load issue context into every session.

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.

Open-source agentic development environment for parallel AI agents

Emdash is a modern content and digital asset management tool designed to help writers, content teams, and publishers organize, write, edit, and manage their content workflows in a streamlined, distraction-free environment. It replaces scattered content across documents, folders, and tools with a unified workspace where teams draft, review, collaborate, and publish written content, prioritizing the craft of writing.

Minimal terminal coding harness

Pi is an open-source minimalist coding agent built by Mario Zechner that runs in the terminal with an intentionally lean design — just four core tools (read, write, edit, bash) and a ~300-word system prompt. It treats the context window as scarce, omits sub-agents and MCP by default, and pushes extensibility to TypeScript extensions, skills, and prompt templates developers build for their own needs. A radical counterpoint to bloated AI coding tools.

Open-source AI coding agent for the terminal

Open-source terminal-based AI coding agent built in Go by the SST team, with a rich TUI (Bubble Tea) supporting 75+ model providers including OpenAI, Anthropic, Gemini, Bedrock, Groq, and OpenRouter. Features vim-like editing, persistent SQLite sessions, and LSP integration for 40+ languages. Fully free with no vendor lock-in, it has rapidly grown to 95k+ GitHub stars.

OpenAI's agentic coding CLI and cloud sandbox

OpenAI's cloud-based AI coding agent powered by codex-1 (a version of o3 optimized for software engineering). Autonomously writes features, fixes bugs, and proposes pull requests, with each task running in its own sandboxed environment preloaded with your repository. Teams can deploy multiple agents in parallel to work on independent tasks, with MCP integration and AGENTS.md for repo-specific instructions.

Persistent memory layer for AI coding agents — keeps Claude Code, Codex, Cursor, and any MCP agent in context across sessions

agentmemory is an open-source MCP server that gives AI coding agents persistent, cross-session memory. Built on hybrid vector-graph search, it achieves 95.2% recall on the LongMemEval-S benchmark while using up to 92% fewer context tokens than naive context injection. Works out of the box with Claude Code, Codex, Cursor, Windsurf, Cline, OpenCode, Kilo Code, Hermes, and any MCP client through 51 MCP tools plus 12 hooks and 4 skills.

Convert any screenshot or mockup into clean frontend code with AI vision.

screenshot-to-code is an open-source tool that converts screenshots, mockups, and Figma designs into clean, functional HTML, Tailwind CSS, React, or Vue code using AI vision models. Powered by GPT-4V, Claude, and Gemini, it supports video-to-code and iterative editing workflows, making it a rapid scaffolding tool for frontend developers who want to skip the pixel-translation step entirely.

MCP, ACP and Skills support for building production coding agents — interactive or automated.

fast-agent is an Apache-licensed Python framework for building and running LLM agents with full MCP (Model Context Protocol) and ACP support. It ships with an interactive shell mode, Skills management, and multi-model routing — making it a practical platform for coding agents, workflow automation, and agent evaluation across Claude, Codex, HuggingFace, and local models.

Vectorless, reasoning-based RAG that reads documents like a human expert — no vector DB, no chunking.

PageIndex is a vectorless, reasoning-based RAG system that builds hierarchical tree indexes from long documents and uses LLMs to navigate them like a human expert would. Instead of chunking text and comparing embeddings, it constructs a table-of-contents-style structure and reasons its way to the right sections — no vector database required. Available as an open-source Python package, cloud API, MCP server, and chat platform.

Library for efficient similarity search and clustering of dense vectors at billion-scale.

FAISS is Meta AI Research's open-source library for efficient similarity search and clustering of dense vectors. It implements approximate nearest-neighbor algorithms designed to scale to billions of vectors, with optimized indexes that fit in RAM and GPU acceleration for the largest workloads. Engineering teams use FAISS as the retrieval primitive underneath custom RAG pipelines, recommendation systems, and large-scale embedding search infrastructure.

Header-only C++ implementation of HNSW for fast approximate nearest-neighbor search.

hnswlib is a header-only C++ library implementing the Hierarchical Navigable Small World (HNSW) graph algorithm for approximate nearest-neighbor search, with Python bindings and a tiny dependency footprint. Originally developed by the nmslib team, it has become the default HNSW implementation embedded inside many vector databases and search products. Engineers use it directly when they want HNSW retrieval without pulling in a heavyweight vector DB.

Open-source post-building layer for agents — tracing, evals, and online monitoring

Judgeval is the open-source post-building layer for AI agents from Judgment Labs, providing OpenTelemetry-based tracing, hosted and custom evaluation scorers, and online behavior monitoring for LLM-powered applications. Instrument any function with a single decorator, score live production traffic against faithfulness and instruction-adherence checks, and feed real-world failures back into reinforcement learning or supervised fine-tuning loops.

Open-source observability and self-healing layer for AI agents

TraceRoot is a YC S25-backed open-source observability platform purpose-built for AI agents and LLM apps. It combines OpenTelemetry-compatible tracing with an agentic debugging runtime that reads your source code, correlates failures with recent commits, and proposes fix PRs automatically. BYOK support spans seven LLM providers; the entire stack runs self-hosted via Docker Compose, with TraceRoot Cloud available for managed deployments.

One tool for intercepting, mocking, and replaying HTTP — acquired by BrowserStack

Requestly is an open-source HTTP interceptor, API client, and session replay tool that lets developers modify, mock, and debug network traffic without leaving the browser. Acquired by BrowserStack and trusted by 200,000+ developers, it bundles a Chrome extension, a full API client, mock servers, and shareable session captures into one free-plus-commercial product.

Open-source visual editor for React — your components, drag-and-drop, no vendor CMS

Puck is an open-source visual page builder for React that gives marketing teams a drag-and-drop editor backed by your own components — no vendor CMS, no proprietary runtime, just your components rendered in a visual canvas. With 12,500+ stars, MIT license, and a small but active team at Measured Co., Puck has become the default self-hosted answer for React-native visual editing.

Rust-native multi-agent orchestration for production

GraphBit is a Rust-native, multi-agent orchestration framework built for production. It targets the gap between Python-first frameworks like LangGraph and the operational expectations of enterprise systems — predictable memory, low latency, deterministic concurrency, and the ability to embed an agent runtime in services that already run Rust without dragging in a Python interpreter.

High-recall Postgres vector search at billion scale

VectorChord is a Postgres extension from TensorChord that brings high-recall vector search to PostgreSQL. As the spiritual successor to pgvecto.rs, it combines IVF indexes with RaBitQ quantization to deliver Pinecone-class performance at billion-vector scale while keeping all data inside a single Postgres database — no separate vector store, no two-system sync, no rewrites when the workload grows.

AI-native database for hybrid RAG retrieval

Infinity is an AI-native database from InfiniFlow that unifies dense vectors, sparse vectors, tensors, and full-text search in a single engine. Built for retrieval-augmented generation (RAG) at scale, it powers hybrid search workflows where lexical matching, semantic similarity, and reranking all happen against one storage layer instead of four loosely coupled services.

Open-source toolkit for building AI SRE incident response agents

OpenSRE is an open-source Python toolkit from Tracer Cloud for building AI SRE agents that investigate and respond to production incidents. It ships with connectors to Prometheus, Grafana, Kubernetes and incident platforms, plus a simulation harness that replays past incidents so teams can benchmark agent accuracy before trusting it on live pager rotations.

Self-evolution engine for AI agents with auditable updates

Evolver is an open-source self-evolution engine for AI agents that turns run logs into auditable, reviewable updates via its Genome Evolution Protocol. Instead of ad hoc prompt tweaking, teams collect traces and Evolver proposes versioned diffs to prompts, tools and workflows that engineers can approve, reject or roll back like code.

Official Chrome DevTools MCP server for coding agents

chrome-devtools-mcp is the Chrome DevTools team's official MCP server that lets coding agents control and inspect a live Chrome browser with first-party Chrome DevTools Protocol fidelity. It exposes Network inspection, Performance traces, Lighthouse audits, console output, and structured DOM snapshots as typed MCP tools, so agents can debug real pages and ship reliable web performance investigations without resorting to brittle DOM scraping.

Self-evolving local computer agent with a reusable skill tree

GenericAgent is a minimal, self-evolving autonomous agent in roughly 3K lines of Python that gives LLMs system-level control of a local computer. It writes files, runs shell commands, and browses the web, but its defining feature is skill crystallization: successful task runs are saved as reusable skills inside a growing skill tree that cuts token cost on repeats.

Open-source async coding agent you can run in your own sandbox

Open-source framework from LangChain AI for building your organization's internal coding agent — the same pattern Stripe's Minions, Ramp's Inspect, and Coinbase's Cloudbot follow. Built on LangGraph and Deep Agents, Open SWE runs each task in an isolated cloud sandbox (Modal, Daytona, Runloop, or LangSmith), invokes from Slack, Linear, or GitHub, orchestrates subagents, and opens pull requests autonomously — customizable end-to-end for your codebase and conventions.