Pick a template, see what it does, get a Dockerfile + docker-compose + bot + README you can run anywhere. Use it as a repeatable review, validation or hardening pass.

The most comprehensive list of AI agents, frameworks, and tools in 2026. 340+ resources across 20+ categories. Updated monthly. Use it to navigate the topic and choose relevant methods, papers or tools.

Indexes any codebase into a knowledge graph — every dependency, call chain, cluster, and execution flow — then exposes it through smart MCP tools so AI agents never miss code. Use it to ground design choices in named patterns, trade-offs and examples.

Reverse-engineered system prompt of Claude Design from Anthropic. A system prompt and skill library that turns an LLM into an opinionated, accessibility-aware, AI-slop-resistant design collaborator.

A self-improving multi-agent orchestration framework for Claude Code, Gemini CLI, and Codex CLI. Coordinate 18 specialized AI agents and 13 orchestration skills through a complete software development lifecycle, from issue to merged PR, with recursive orchestration, parallel review gates, and a git-native knowledge base.

This is a starter template for LiveKit Agents that provides a simple voice interface using Agents UI components and LiveKit JavaScript SDK. It supports voice, transcriptions, and virtual avatars.

English | 中文 HomeRail is a TypeScript runtime that turns one-off agent chats into auditable, reusable workflows. The name comes from what it is: Home — it runs on your own homelab, NAS, or home server, serving the people who live there; Rail — the track shape of a DAG, where agent work flows node to node along explicit edges instead of pooling in a single chat.

A collection of AI agent skills focused on resume optimization, job applications, and career development. Built for job seekers, career changers, and professionals who want Claude Code to help with resume writing, ATS optimization, interview prep, and strategic job search.

Semantic Intelligence for Large-Scale Engineering. Context+ is an MCP server designed for developers who demand 99% accuracy.

Prompt with an image/video → Get runnable vision code → Build Visual AI App in minutes Discord · Architecture · YouTube VisionAgent is the Visual AI pilot from LandingAI. Give it a prompt and an image, and it automatically picks the right vision models and outputs ready‑to‑run code—letting you build vision‑enabled apps in minutes.

Robust Go framework for building intelligent multi-agent AI systems The most productive way to build AI agents in Go. AgenticGoKit provides a unified, streaming-first API for creating intelligent agents with built-in workflow orchestration, tool integration, and memory management.

A collection of prompts for AI-assisted development with Claude Code. https://www.youtube.com/watch?v=KVOZ9s1S9Gk&lc=UgzfwxvFjo6pKEyPo1R4AaABAg Found value in these resources?

This repository is a collection of reference implementations for the Model Context Protocol (MCP), as well as references to community-built servers and additional resources. The servers in this repository showcase the versatility and extensibility of MCP, demonstrating how it can be used to give Large Language Models (LLMs) secure, controlled access to tools and data sources.

• Documentation • PowerShell-Native AI Agents & Multi-Agent Orchestration PSAI is a high-agency framework designed to bridge the gap between robust systems engineering and Large Language Models. Built for developers and architects, it transforms AI from a "chatbot" into a functional engineering component within your existing PowerShell ecosystem.

Version, test, and monitor every prompt and agent with robust evals, tracing, and regression sets. --- This library provides convenient access to the PromptLayer API from applications written in python.

Agentic Document Extraction (ADE), from your terminal. The ade command drives LandingAI's ADE v2 document APIs — parse turns visually complex documents (tables, figures, charts) into grounded markdown and elements; extract pulls schema-shaped fields with page-and-box evidence — and persists everything it produces in a local store (~/.ade), serving every read from it.

go-agent is a Go framework for building AI agents with pluggable LLM providers, memory, file context, guardrails, UTCP tool orchestration, and multi-agent coordination. Use it when you want agent runtime pieces that stay idiomatic in Go: For this repository: The module currently targets Go 1.25.10.

Solace Agent Mesh Open-source framework for building event driven multi-agent AI systems Star ⭐️ this repo to stay updated as we ship new features and improvements. Key Features • Quickstart • Next Steps • Docs --- Solace Agent Mesh is a framework that supports building AI applications where multiple specialized AI agents work together to solve complex problems.

) Docs · Playground · LandingAI The official Python library for the LandingAI Agentic Document Extraction (ADE) API. Parse PDFs and images into structured, grounded Markdown, then extract typed fields with a JSON Schema or Pydantic model.

A self-learning data agent built with systems engineering principles. It grounds answers in 6 layers of context and improves with every query.