Welcome to LangCrew

From CrewAI simplicity to LangGraph power - the only framework you need for production-ready AI agent systems

Python 3.10+Built on LangGraphProduction Ready

Why Choose LangCrew?

The best of both worlds: CrewAI’s simplicity meets LangGraph’s enterprise capabilities

Beyond Traditional Flexible Paradigms

Revolutionary agent collaboration: Provides a simple, highly configurable development experience with powerful built-in mechanisms like HITL, dynamic workflow orchestration, and event-driven processes that empower unprecedented agent coordination.

Full-Stack Support for Productization

Accelerate market delivery: Complete Agent-UI protocol and React component library enable frontend visualization of agent planning, scheduling, execution, and tool invocation—significantly reducing time from development to production deployment.

Application Templates for Fast Launch

Industry-ready solutions: Rich variety of production-tested templates enabling rapid prototyping and deployment of multi-agent solutions across diverse industries and scenarios—from concept to market in record time.

Integrated Development and Operations Support

Seamless lifecycle management: Integrated free SaaS services covering system construction, deep observability, sandbox environments, and deployment resources—simplifying the entire journey from development to operations.

Framework Comparison

Aspect	LangGraph	CrewAI	LangCrew
Abstraction	Low-level primitives	High-level patterns	High-level on LangGraph
Development	Build from scratch	Simple but limited	Best practices pre-built
HITL	Basic interrupt/resume	Limited support	Advanced approval system + bilingual UI
Memory	Complete primitives/docs	Simple context	LangGraph native + langmem integration
Tools	LangChain only	Custom only	Unified registry + LangCrew-Tools
UI	None	Basic examples	Full React components
Observability	LangSmith integration	Enterprise edition	LangSmith + LangTrace integration
Deployment	Platform available	Enterprise edition	Platform (Coming Soon)

Quick Start Example

Build your first agent crew in under 5 minutes:

# Install LangCrew
pip install langcrew

# Set up your LLM API key
export OPENAI_API_KEY=your_openai_key

from langcrew import Agent, Crew, Task
from langcrew.project import CrewBase, agent, crew, task
from langchain_openai import ChatOpenAI

# Configure LLM
llm = ChatOpenAI(model="gpt-4o")

@CrewBase
class ResearchCrew:
    @agent
    def researcher(self) -> Agent:
        return Agent(
            role="Market Researcher",
            goal="Find latest trends in AI automation",
            tools=["web_search"],  # Built-in tools
            backstory="Expert at finding market insights",
            llm=llm
        )

    @task
    def research_task(self) -> Task:
        return Task(
            description="Research AI automation trends for {topic}",
            agent=self.researcher(),
            expected_output="Detailed market analysis report"
        )

    @crew
    def crew(self) -> Crew:
        return Crew(
            agents=self.agents,
            tasks=self.tasks,
            memory=True,  # Enable memory
            verbose=True  # See execution details
        )

# Run the crew
result = ResearchCrew().crew().kickoff(
    inputs={"topic": "enterprise AI adoption"}
)

Getting Started Paths

Quick Start Guide

New to LangCrew? Begin with installation and build your first agent crew in minutes with our step-by-step guide.

Quick Start →

Core Concepts

Understand the framework Learn about Agents, Tasks, Crews, and the foundational concepts that power multi-agent collaboration.

Agents → | Tasks → | Crews →

Advanced Features

Ready for production? Master memory systems, human-in-the-loop workflows, tools integration, and web services.

Memory Guide → | HITL Guide →

Production Deployment (Coming Soon)

Scale your applications Advanced deployment features, enterprise observability, and production-grade configurations are being developed.

Web Services → | Tools →

Success Stories

“LangCrew reduced our development time from weeks to days. The production templates and UI components are game-changers.”
— Sarah Chen, Lead AI Engineer at TechCorp

“Finally, a framework that bridges the gap between prototyping and production. The HITL features are exactly what we needed.”
— Alex Rodriguez, CTO at StartupAI

Ready to build production-ready AI agent systems?
Get Started →Star on GitHub →