A curated list of awesome projects, resources, and tools for building stateful, multi-actor applications with LangGraph.
Welcome to Awesome LangGraph! This repository is your go-to resource for discovering tools, templates, and examples for building powerful AI applications with LangGraph. Whether you're just getting started or building production-ready systems, you'll find valuable resources to accelerate your development.
- Core Ecosystem
- Official Resources
- Community Projects
- Learning Resources
- Companies Using LangGraph
- Contributing
- Acknowledgments
LangGraph extends the LangChain ecosystem to provide flexible orchestration for LLM-powered systems. The ecosystem consists of several key components working together to support the entire LLM application lifecycle:
Source: LangChain Documentation
LangChain
- Foundation framework for LLM application development
- Provides standardized interfaces for LLMs and related technologies
- Includes extensive integrations with embedding models and vector stores
- Features reusable components for chains, agents, and memory systems
📚 Documentation: Python | TypeScript
LangGraph
- Built on top of LangChain for advanced workflow orchestration
- Enables building stateful, multi-agent systems
- Provides first-class streaming support
- Includes built-in human-in-the-loop capabilities
- Supports complex agent interactions and coordination
📚 Documentation: LangGraph Docs | TypeScript Docs
LangSmith
- Comprehensive observability and debugging platform
- Debugging and testing tools
- Playground for experimentation
- Prompt management and versioning
- Annotation and evaluation
- Performance monitoring
- Testing automation
📚 Documentation: LangSmith Platform | LangSmith Docs
LangGraph Platform
- Production deployment and management solution
- API generation for LangGraph applications
- Deployment automation
- Scaling infrastructure
- Production monitoring
📚 Documentation: Platform Overview
More details about the platform components and features in the section below.
The LangGraph Platform provides tools and services for building, deploying, and managing production-grade applications:
Source: LangGraph Platform Documentation
LangGraph Server
- Opinionated API architecture for deploying agentic applications
- Built-in support for streaming, background runs, and task queues
- Horizontally scalable infrastructure
- Integrated monitoring with LangSmith
📚 Documentation: Server Docs
LangGraph Studio
- Visual IDE for development and debugging
- Real-time graph visualization
- Interactive testing environment
- Integrated debugging tools
📚 Documentation: Studio Docs
LangGraph CLI
- Command-line interface for local development
- Project scaffolding and management
- Deployment automation
- Configuration management
📚 Documentation: CLI Docs
LangGraph SDK
- Core development toolkit
- Graph construction and management
- State management utilities
- Integration helpers
📚 Documentation: SDK Docs
Remote Graph
- Remote execution of deployed applications
- Seamless integration with deployed servers
- State synchronization
- Distributed execution support
📚 Documentation: Remote Graph Guide
Templates to help you get started with LangGraph. For deployment instructions, check out the LangGraph CLI Documentation.
| Template | Description |  |
 |
|---|---|---|---|
| New Project | Basic chatbot with memory | langchain-ai/new-langgraph-project | langchain-ai/new-langgraphjs-project |
| ReAct Agent | Tool-using agent framework | langchain-ai/react-agent | langchain-ai/react-agent-js |
| Memory Agent | Cross-thread memory persistence | langchain-ai/memory-agent | langchain-ai/memory-agent-js |
| Retrieval Agent | Knowledge-based QA system | langchain-ai/retrieval-agent-template | langchain-ai/retrieval-agent-template-js |
| Data Enrichment | Web search & data organization | langchain-ai/data-enrichment | langchain-ai/data-enrichment-js |
LangGraph comes with a built-in React agent pattern, and the community has developed numerous additional agent libraries. Below are some of the most popular community-built options that extend LangGraph's functionality in various ways.
These are the official agents provided and maintained by LangGraph:
| Agent | Description | |
|
|---|---|---|---|
| Computer Use Agent | Agent for automating computer interactions and tasks | langgraph-cua-py | langgraph-cua |
| Swarm Agent | Build swarm-style multi-agent systems | langgraph-swarm-py | langgraph-swarm |
| Supervisor | Build supervisor multi-agent systems | langgraph-supervisor-py | langgraph-supervisor |
| MCP Adapters | Make Anthropic MCP tools compatible with agents | langchain-mcp-adapters | ❌ |
| LangMem | Agents that learn and adapt from interactions | langmem | ❌ |
| CodeAct | Advanced function-calling with code generation | langgraph-codeact | ❌ |
| Reflection | Agent architecture with self-review capabilities | langgraph-reflection | ❌ |
| BigTool | Build agents with large numbers of tools | langgraph-bigtool | ❌ |
These applications demonstrate real-world implementations using LangGraph. From chatbots to content generation, each example showcases different patterns and best practices for building production-ready systems and can be deployed with LanGraph Cloud.
You can use these as reference architectures or starting points for your own projects.
| Name | Description |
|---|---|
ChatLangChain |
Documentation assistant powered by RAG-based semantic search with intelligent query analysis. Features automated content indexing, duplicate prevention, GenUI, and sophisticated document tracking system. |
OpenGPTs |
Open-source GPT alternative supporting 60+ LLM providers and tools. Implements three cognitive architectures (Assistant, RAG, Chatbot) with PostgreSQL backend and flexible deployment options. |
Executive AI Assistant |
Smart email management system with calendar integration. Provides intelligent triage, automated response drafting, and meeting coordination through Gmail API with customizable workflows. |
Agent Inbox |
Centralized interface for AI agent interactions featuring real-time communication, interrupt handling, and configurable response systems for both local and cloud deployments. |
Python Fullstack |
All-in-one chatbot template combining React-style agents with modern UI. Built with FastHTML components and Claude 3, featuring single-deployment architecture and extensible tools. |
LangGraph UI Examples |
Showcase of generative UI agents including stockbroker, trip planner, and email tools. Demonstrates human-in-the-loop workflows with customizable components and tool integrations. |
LangChain Next.js |
Next.js starter template showcasing LangChain.js modules. Includes streaming chat, structured output, multi-step agents, and RAG implementations with Vercel AI SDK integration. |
Custom Auth |
Supabase-powered authentication template for LangGraph deployments. Implements OAuth2 with Google, user management, and secure chatbot access with conversation thread isolation. |
Gen UI Computer Use |
A Generative UI web app for interacting with Computer Use Agents (CUA) via the @langchain/langgraph-cua prebuilt package. Features a modern interface for computer automation and task management. |
LangGraph provides official development tools to streamline your workflow, from visual design to code generation. These tools help you build and deploy LangGraph applications more efficiently.
- LangGraph Builder – Visual canvas for designing cognitive architectures of LangGraph applications with code generation for Python and TypeScript
- LangGraph Generator – CLI tool for generating LangGraph application stubs from YAML specifications
Access official documentation in LLM-readable formats, enabling LLMs and agents to understand and work with the frameworks, particularly within integrated development environments (IDEs). Learn more in the official documentation.
| Framework | Index File | Full Documentation |
|---|---|---|
| LangGraph Python | llms.txt | llms-full.txt |
| LangGraph JS | llms.txt | llms-full.txt |
| LangChain Python | llms.txt | - |
| LangChain JS | llms.txt | - |
The llms.txt files serve as lightweight indexes for quick reference, while llms-full.txt provides comprehensive documentation for deeper understanding and integration.
Ready-to-use integrations for extending LangGraph with external services and tools. Access everything from LLMs, vector stores to databases to development tools.
🔗 Python Packages | 🔗 JavaScript Packages
This is a curated list of open-source agent and LLM projects. They are grouped by category for easier discovery.
- TrustCall - Tenacious tool calling built on LangGraph
- Data Science Team - AI-powered data science team for common tasks
- Delve - A taxonomy generator for unstructured data
- Nodeology - Enable researcher to build scientific workflows easily with simplified interface
- Breeze Agent - A streamlined research system built inspired on STORM and built on LangGraph
Want to contribute your own pre-built agent? Check out the contribution guidelines in the documentation.
- AI-Data-Analysis-MultiAgent – Multi-agent system for data analysis, visualization, and report generation.
- AI Coding Assistant – Development tool that uses LangGraph agents to aid coding workflow with natural language.
- Brainstormers – Tool with curated, optimized chains for brainstorming using real-world techniques.
- Clevrr Computer – Automation agent for basic computer tasks with a focus on safety and accuracy.
- ContentMind AI – Turns websites into LLM-ready research content with automated documentation indexing.
- CopilotKit – Framework for building AI copilots with generative UI, chat interfaces, and human-in-the-loop capabilities
- RD-Agent – Microsoft's R&D automation tool for data mining, paper analysis, and model tuning.
- WebRover – Autonomous AI agent for automating web tasks and research.
- AI Conversation Simulator – Test and develop AI assistants through simulated conversations with configurable personas and LangSmith integration
- SurfSense – Customizable AI research agent that integrates personal knowledge bases with external sources like Tavily, Slack, and Notion
- RAI – Flexible multi-agent framework for developing and deploying Embodied AI features in robotics with multi-modal interaction support
- AI Agent Service Toolkit – Framework for deploying AI agents with FastAPI and Streamlit.
- Browser Use: Web AI – Library for AI agents to interact with websites and automate web tasks.
- Khoj – Self-hostable AI second brain for web or docs with custom agents.
- Hyperbolic-AgentKit – AI agent framework with blockchain and compute features.
- Agent Protocol – Codified, framework-agnostic APIs for serving LLM agents in production.
- SRAgent – Multi-agent framework for automating genomic research and RNA sequencing workflows from scientific databases.
- Google GenAI Toolbox – Production-grade infrastructure for connecting AI agents with databases, featuring security, observability, and connection pooling
- LangGraph MCP Agents – Toolkit for integrating Model Context Protocol (MCP) with LangGraph agents, featuring Streamlit interface, dynamic tool management, and real-time streaming responses.
- AgentWrite – Automated content generation tool that breaks down writing tasks.
- Podcastfy.ai – Transforms multi-modal content into audio conversations in multiple languages.
- Robo-blogger – Voice-to-content pipeline for converting spoken ideas into structured blog posts.
- Social Media Agent – Generates Twitter & LinkedIn posts from URLs with optional human review.
- YT Navigator – AI-powered tool for efficient navigation and search through YouTube channel content
- bRAG – Tutorial series on RAG (Retrieval Augmented Generation) from basics to advanced.
- Demo Bank Support Bot – RAG-powered banking support chatbot designed to prevent hallucinations.
- Denser Chat – Chatbot that answers questions from PDFs and webpages with text extraction.
- IdentityRAG Insights – Chatbot that merges customer data into golden records for context-aware replies.
- King RAGent – AI research assistant with PDF processing, vector storage, and web search integration.
- Reply gAI – AI clone for X/Twitter profiles with long-term memory and RAG.
- Shandu – LLM-based research system that automates source evaluation and knowledge synthesis.
- Local Deep Research – Privacy-focused research assistant performing deep analysis using multiple LLMs and web searches with local execution capability
- GPT Researcher – Open deep research agent producing detailed reports with citations, using Plan-and-Solve and RAG techniques
- AI Case Study Analyzer - Discovers and analyzes enterprise AI case studies.
- AI Hedge Fund - Six AI agents collaborating through LangChain for smart trading decisions.
- gotoHuman Lead Agent - AI-powered sales solution for automated personalized email drafting with human oversight.
- GreenMe – AI sustainability guide that analyzes lifestyle for carbon footprint reduction.
- Introduction to LangGraph - Official course covering fundamentals and practical use cases.
- LangGraph - Develop LLM powered AI agents - Course on building AI agents with LangGraph by @emarco177
- GenAI_Agents - Agent implementation examples
- RAG_Techniques - Several RAG implementations and tutorials
- Grounding RAG Applications Workshop - Hands-on workshop building RAG chatbots and travel planning agents with JavaScript and Elasticsearch
A comprehensive list of organizations using LangGraph in production environments. For more details and case studies, visit the official adopters page.
| Company | Industry | Use Case | Reference |
|---|---|---|---|
| Social Media | Code generation; Search & discovery | Blog post, 2025 | |
| Uber | Transportation | Developer productivity; Code generation | Presentation, 2024 |
| GitLab | Software & Technology | Code generation | Duo workflow docs |
| Klarna | Fintech | Copilot for domain-specific task | Case study, 2025 |
| Rakuten | E-commerce / Fintech | Copilot for domain-specific task | Blog post, 2025 |
| Minimal | E-commerce | Customer support | Case study, 2025 |
| Komodo Health | Healthcare | Copilot for domain-specific task | Blog post |
| OpenRecovery | Healthcare | Copilot for domain-specific task | Case study, 2024 |
| AppFolio | Real Estate | Copilot for domain-specific task | Case study, 2024 |
| Cisco Outshift | Software & Technology | DevOps | Blog post, 2025 |
| Elastic | Software & Technology | Copilot for domain-specific task | Blog post, 2025 |
| Infor | Software & Technology | GenAI embedded product experiences; customer support; copilot | Case study, 2025 |
| AirTop | Software & Technology (GenAI Native) | Browser automation for AI agents | Case study, 2024 |
| Athena Intelligence | Software & Technology (GenAI Native) | Research & summarization | Case study, 2024 |
| Captide | Software & Technology (GenAI Native) | Data extraction | Case study, 2025 |
We welcome contributions to this awesome list! Please ensure your submission:
- Includes a clear description of its purpose and value
- Follows the existing format and style
- Is placed in the appropriate category
To contribute:
- Fork the repository
- Add your project following the established format
- Create a pull request with a brief explanation
For questions or suggestions, please open an issue.
Special thanks to the @langchain-ai team for building such an amazing framework and ecosystem that enables developers to create powerful AI applications.
This list is inspired by awesome-langchain, which has been a great resource for the community.