deepagents and langgraph-agents
These tools are competitors, as both aim to provide production-ready multi-agent systems built with LangGraph, forcing a choice between their respective implementations and feature sets.
About deepagents
langchain-ai/deepagents
Deep Agents is an agent harness built on langchain and langgraph. Deep Agents are equipped with a planning tool, a filesystem backend, and the ability to spawn subagents - making them well-equipped to handle complex agentic tasks.
Built on LangGraph, it provides automatic context management through conversation summarization and output-to-file routing, plus shell execution with optional sandboxing and MCP (Model Context Protocol) integration for extensible tool ecosystems. The agent returns a compiled LangGraph graph, enabling production features like streaming, persistence, and checkpointing without additional orchestration. Smart defaults include task planning with progress tracking and hierarchical sub-agent delegation with isolated context windows, reducing boilerplate while remaining fully customizable via tools, prompts, and model swapping.
About langgraph-agents
shamspias/langgraph-agents
A production-ready, scalable multi-agent system built with LangGraph, featuring specialized agents for different tasks with best coding practices.
Scores updated daily from GitHub, PyPI, and npm data. How scores work