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deepagents is a standalone library for building agents that can tackle complex, multi-step tasks. Built on LangGraph and inspired by applications like Claude Code, Deep Research, and Manus, deep agents come with planning capabilities, file systems for context management, and the ability to spawn subagents. The deepagents library contains:
  • Deep Agents SDK: A package for building agents
  • Deep Agents CLI: A coding tool built on top of the deepagents package

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When to use deep agents

Use the Deep Agents SDK when you want to build agents that can:
  • Handle complex, multi-step tasks that require planning and decomposition
  • Manage large amounts of context through file system tools
  • Delegate work to specialized subagents for context isolation
  • Persist memory across conversations and threads
For building simpler agents, consider using LangChain’s create_agent or building a custom LangGraph workflow.

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When to use Deep Agents CLI

Use the Deep Agents CLI when you want to use an interactive deep agent on the command-line for coding or other tasks:
  • Customize agents with skills and memory.
  • Teach agents as you use them about your preferences, common patterns, and custom project knowledge.
  • Execute code on your machine or in sandboxes.

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Core capabilities

Planning and task decomposition

Deep agents include a built-in write_todos tool that enables agents to break down complex tasks into discrete steps, track progress, and adapt plans as new information emerges.

Context management

File system tools (ls, read_file, write_file, edit_file) allow agents to offload large context to in-memory or filesystem storage, preventing context window overflow and enabling work with variable-length tool results.

Subagent spawning

A built-in task tool enables agents to spawn specialized subagents for context isolation. This keeps the main agent’s context clean while still going deep on specific subtasks.

Long-term memory

Extend agents with persistent memory across threads using LangGraph’s Memory Store. Agents can save and retrieve information from previous conversations.

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Relationship to the LangChain ecosystem

Deep agents is built on top of:
  • LangGraph - Underlying graph execution and state management
  • LangChain - Tools and model integrations
  • LangSmith - Observability, evaluation, and deployment
Deep agents applications can be deployed via LangSmith Deployment and monitored with LangSmith Observability.

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Get started

SDK Quickstart

Build your first deep agent

Customization

Learn about customization options for the SDK

Middleware

Understand the middleware architecture

CLI

Use the Deep Agents CLI

Reference

See the deepagents API reference
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