Model-agnostic plug-n-play LangChain/LangGraph agents powered entirely by MCP tools over HTTP/SSE.

The definitive resource for Agent Skills - modular capabilities revolutionizing AI agent architecture

Hands-on crash course for Claude Code with branch-based projects on MCP, subagents, hooks, and automation.

Creating 'deep agents' to encourage LLM's to complete long horizon tasks.

Deep Competitive Analyst is a 'deep agent' style LLM assistant built to automate the creation of company profiles and competitive analyses

Stop building AI agents from scratch. Bootstrap starter Agent app with LangGraph, CopilotKit, and beautiful generative UIs.

Experimental AI system for financial applications

Benchmarking llm agents for local usage

Deep Agent: lightweight Python framework for automating complex tasks.

Visualizing Deep Agents in Long-Horizon Tasks: Towards Explainable and Trustworthy Agentic AI

deepagents-showcase is a hands-on project demonstrating how to build hierarchical, multi-step AI systems using LangChain’s Deep Agents. It showcases task decomposition, planning, sub-agent delegation, and long-running workflows in a practical, real-world setup.

Deep Agent Harness Automation System - LangGraph-powered MCP server for infrastructure orchestration with autonomous subagents

Deep Agents CLI skill for LangGraph Deep Agents

Multi-loop LangGraph research agent with Gemini 2.5 Flash + Tavily that searches, reflects, and outputs markdown reports.

Deep Agentsライブラリのアーキテクチャを活用した、ハーネス構成のRAGシステムです。複数のエージェントが協調動作し、質問の粒度に応じて最適なRAGシステム（Naive RAG / ColBERT RAG）を自動選択します。