Skip to content
Back to skills

Deepagents Langchain

ASecurity

DeepAgents — production-ready LangGraph agent framework by LangChain. Batteries-included: planning (write_todos), filesystem ops, shell execution, sub-agents with isolated context, auto context summarization. pip install deepagents → create_deep_agen

  • 14 stars
  • 0 votes
  • 0 copies
  • 1 view
  • Added June 3, 2026
ai-agentspythongoshellgit

Works with

  • mcp

Security analysis

A92/100
  • mediumInstalls packages at runtime which could introduce malicious dependencies

Pro shows the line behind each finding and how to fix it

Scanned June 3, 2026

npx -y skills add mahmoud20138/Tradecraft --skill deepagents-langchain --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Deepagents Langchain?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Deepagents Langchain
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/mahmoud20138-deepagents-langchain/badge)](https://www.skillsdirectory.com/skills/mahmoud20138-deepagents-langchain)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: deepagents-langchain
description: DeepAgents — production-ready LangGraph agent framework by LangChain. Batteries-included: planning (write_todos), filesystem ops, shell execution, sub-agents with isolated context, auto context summarization. pip install deepagents → create_deep_agen
kind: agent
category: ai/agents
status: active
tags: [ai-agents, deepagents, langchain]
related_skills: [agent-development, ai-agent-builder]
---

# deepagents-langchain

USE FOR:
  - "production-ready agent with LangGraph"
  - "batteries-included coding/research agent"
  - "sub-agents with isolated context windows"
  - "LangChain agent framework"
  - "agent with planning + filesystem + shell"
  - "MCP tools in LangGraph agent"
tags: [LangGraph, LangChain, agent, production, sub-agents, MCP, planning, filesystem, shell, open-source]
kind: framework
category: ai-agent-builder

---

## What Is DeepAgents?

Production-ready, batteries-included LangGraph agent by LangChain.
No manual setup — `create_deep_agent()` returns a fully functional agent.

- Repo: https://github.com/langchain-ai/deepagents
- Install: `pip install deepagents`
- Framework: **LangGraph** (compiled graph, streaming, persistence, checkpointing)
- LangGraph Studio compatible

---

## Quick Start

```python
pip install deepagents
```

```python
from deepagents import create_deep_agent

agent = create_deep_agent()
result = agent.invoke({
    "messages": [{"role": "user", "content": "Research the latest AI agent frameworks and summarize"}]
})
print(result["messages"][-1].content)
```

---

## Built-in Capabilities

| Capability | Tools Included |
|-----------|---------------|
| **Planning** | `write_todos` — task decomposition + progress tracking |
| **Filesystem** | read, write, edit, search files |
| **Shell** | execute commands (with sandboxing) |
| **Sub-agents** | delegate tasks with isolated context windows |
| **Context** | auto-summarization, large output → file handling |

---

## Architecture (LangGraph)

```python
# Returns a compiled LangGraph graph
agent = create_deep_agent()

# Supports all LangGraph features:
# - Streaming
for chunk in agent.stream({"messages": [("user", "task")]}):
    print(chunk)

# - Persistence / checkpointing
from langgraph.checkpoint.memory import MemorySaver
agent = create_deep_agent(checkpointer=MemorySaver())

# - LangGraph Studio compatibility (visual debug)
```

---

## Customization

```python
from deepagents import create_deep_agent
from langchain_anthropic import ChatAnthropic

# Custom model
agent = create_deep_agent(
    model=ChatAnthropic(model="claude-opus-4-6")
)

# Add custom tools
from langchain_core.tools import tool

@tool
def my_tool(query: str) -> str:
    """Custom tool description"""
    return do_something(query)

agent = create_deep_agent(tools=[my_tool])

# Custom system prompt
agent = create_deep_agent(
    system_prompt="You are an expert financial analyst..."
)
```

---

## MCP Integration

```python
from langchain_mcp_adapters import MCPToolkit

# Connect any MCP server
toolkit = MCPToolkit(server_command=["npx", "gitnexus", "mcp"])
mcp_tools = toolkit.get_tools()

agent = create_deep_agent(tools=mcp_tools)
```

---

## Sub-Agents Pattern

```python
# Main agent delegates to sub-agents with isolated contexts
# Sub-agents don't share main agent's conversation history
# Useful for: parallel research, isolated code execution

agent = create_deep_agent(
    enable_subagents=True,
    subagent_model=ChatAnthropic(model="claude-haiku-4-5-20251001")  # cheaper for subtasks
)
```

---

## Use Cases

- **Research pipeline**: fetch + summarize + synthesize across sources
- **Code automation**: read codebase → plan changes → edit files → run tests
- **Data processing**: ingest files → transform → write outputs
- **Multi-step workflows**: plan → delegate subtasks → aggregate results

---

## vs. Other Agent Frameworks

| Feature | DeepAgents | OpenAlice | AutoHedge |
|---------|-----------|-----------|-----------|
| Framework | LangGraph | Custom TS | Swarms |
| Built-in tools | ✓ (full) | ✓ (trading) | ✓ (trading) |
| Sub-agents | ✓ | ✗ | ✗ |
| MCP support | ✓ | ✓ (planned) | ✗ |
| Domain | General | Trading | Trading |
| Studio UI | ✓ LangGraph | ✓ Web | ✗ |


---

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.