A skills set and methodology for coding agents: clarify the task, plan, write tests, then code. The agent works with more discipline.
The AI movement's repository database
The best AI repositories
224 living projects — from agent frameworks to prompt-injection defense. Each comes with our own note: why it matters, who it is for and how to start in three steps.
Stars, forks and activity refresh daily via the GitHub API · updated October 6, 2026
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A service that turns any website into clean Markdown or structured data for models. It can search, scrape, crawl a whole site and even click through a page.
A small Microsoft utility that converts PDF, Word, PowerPoint, Excel and other files into Markdown that is easy to hand to a language model.
An open coding agent for the terminal with a desktop app. It is not tied to one provider: plug in whichever models you have.
A toolkit for spec-driven development: principles and a spec first, then a plan and tasks, and only then code. Works with several coding agents.
OpenAI's lightweight coding agent that runs in the terminal and works on your project's code. Written in Rust.
Categories
Agent frameworksFrameworks and orchestration: what agents and multi-agent systems are built from.23 repositoriesCoding agents & CLIAgents that write code in the terminal and editor, and the methods for working with them.21 repositoriesMCPThe Model Context Protocol spec, official SDKs and the best servers.20 repositoriesOpen models & inferenceOpen weights, local runs, fast inference and fine-tuning.38 repositoriesRAG & vector DBsSearch over your own data: document parsing, crawlers, vector databases, knowledge graphs.19 repositoriesEvals & observabilityHow to measure a model or agent and see what happens inside it.17 repositoriesPrompting & contextPrompts, structured output, skills and context engineering.16 repositoriesVoice, video, multimodalSpeech recognition and synthesis, voice agents, images and video.19 repositoriesAutomationNo-code workflows, browser and computer-use agents.15 repositoriesAwesome lists & learningCourses, books and awesome lists worth starting with.21 repositoriesSecurityPrompt injection, guardrails, red teaming and agent scanners.15 repositoriesMissing your favorite?Suggest a repository — we will review it and add it if it earns a spot.Suggest a repo →
Catalog
50 repositories
An open coding agent for the terminal with a desktop app. It is not tied to one provider: plug in whichever models you have.
A platform where you build agents in a visual builder or by describing them in plain words, then run them on a schedule or a trigger. Hosted version plus free self-hosting.
The best-known toolkit for LLM apps: one interface to dozens of models, plus tools, chains and agents. You can swap providers without rewriting the app.
A node-based builder for diffusion pipelines: wire up image, video and audio generation visually. Runs locally and exposes API endpoints.
Code for Sebastian Raschka's book: you build a GPT-like model in PyTorch step by step, then pretrain and finetune it. The best way to see how an LLM works inside.
An animation engine Grant Sanderson uses to make 3Blue1Brown videos, including the well-known neural network ones. It is not an AI library but a tool for explaining math and ML visually.
A fast multiplayer code editor in Rust from the creators of Atom and Tree-sitter, with built-in AI agent support. A lightweight alternative to VS Code.
A detailed guide to prompt engineering: techniques from few-shot to chains of thought, papers, lectures and notebooks. Recently extended with context engineering and agents.
A collection of examples and guides for the OpenAI API: from basic requests to function calling and RAG. Most code is Python.
An autonomous coding agent in three forms: IDE extension, CLI and SDK. It can run in the background, on a schedule and from chat apps.
More than 60 PyTorch implementations of research papers with notes next to the code: transformers, optimizers, GANs, reinforcement learning. The website shows code and notes side by side.
A single gateway to 100+ LLM providers in OpenAI format: a Python SDK and a proxy server with cost tracking, load balancing and logging. Swap models without changing code.
A curated list of skills, subagents, plugins, status lines and tools for Claude Code. A handy map of the ecosystem around the coding agent.
An open, extensible agent that goes beyond code: research, writing, automation. Works with 15+ providers and 70+ extensions through MCP.
An agile AI-driven development method: a set of role agents (analyst, architect, developer and more) and a process from idea to code. Installs as skills or a plugin.
A local replacement for cloud APIs: an OpenAI-compatible server that runs text, voice and image models on any hardware, no GPU required.
One of the first terminal AI pair programmers: it edits your repo's files and makes git commits itself. Works with almost any model.
Meta's classic library for fast similarity search and clustering of vectors. It is not a database but an index engine that many other systems are built on.
A catalog of AI agent use cases by industry: healthcare, finance, education, retail. Each use case links to an open-source project.
An open coding agent as a VS Code extension, JetBrains plugin and CLI. The repo is frozen: version 2.0.0 was the final release, and the code now serves as a reference.
The standard PyTorch library for diffusion models: ready-made pipelines for images, video and audio that run in a few lines.
A free Hugging Face course on agents in four units: fundamentals, the smolagents, LlamaIndex and LangGraph frameworks, agentic RAG and a final benchmark assignment.
A toolkit for coding agents that works with code semantically: finds symbols and references and edits through language servers instead of rereading whole files. Saves context on large projects.
More than 40 runnable notebooks with RAG techniques, from basic retrieval to advanced setups. Each one has the idea, the code and references.
The easiest vector database to start with: it runs inside your app process, stores documents and finds similar ones. Great for prototypes, with a client-server mode and a cloud.
A TypeScript framework for agents and AI apps: agents, workflows, memory and quality evaluation in one place. A good fit for Node-based web teams.
A Python framework that hides the protocol plumbing: a decorated function becomes an MCP tool. The shortest path from idea to a working server.
An open agentic-engineering platform: CLI, IDE plugins and a cloud. One of the most popular open-source coding agents.
The AI SDK from the makers of Next.js: one TypeScript interface to models, streaming, tool calling and React hooks. Switching providers takes one line.
Twelve principles for building LLM apps good enough to put in customers' hands: own your prompts, own your context, small agents, explicit control flow.
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