Build resilient language agents as stateful graphs with cycles, branching, and persistence
Key Features
Multi-Agent
Single Agent
Human-in-the-Loop
Streaming
Async Support
Type Safe
Short-Term Memory
Long-Term Memory
Shared Memory
Plugin System
Custom Tools
MCP Protocol
A2A Protocol
Code Execution
Web Browsing
File System Access
Sandboxing
Guardrails
Structured Output
DAG Workflows
Visual Builder
CLI
API Server
Self-Hosted
Cloud Hosted
Community Feedback
Strengths
- Controllable multi-agent flows
- Durable execution surviving failures
- Human-in-the-loop support
- Graph-based fine-grained control
Weaknesses
- Requires understanding graph concepts
- Tightly coupled to LangChain ecosystem
- Newer project with evolving API
LangGraph Details
| Organization | LangChain Inc |
| Organization Type | Company |
| Funding | Series b+ |
| Category | Framework |
| Subcategory | Orchestration |
| Deployment | Hybrid |
| Primary Language | Python |
| Runtime | Python 3.9+ |
| License | MIT |
| Commercial Use | Unrestricted |
| Install Command | pip install langgraph |
| GitHub Stars | 27,370 |
| GitHub Forks | 4,706 |
| Release Cadence | Weekly |
| Maturity | Stable |
| Pricing Model | Open core |
| Free Tier | MIT-licensed core is free |
| Self-Hosted Free | Yes |
| Cost Model | free + LLM costs |
| Community Size | Large |
| Community Activity | Very active |
| Sentiment | Positive |
| GPU Required | No |
| Confidence | High |
| Research Date | 2026-03-24 |
| LLM Providers | All via LangChain |
| API Keys Required | LLM provider API key |
Use Cases
- Complex multi-agent workflows
- Human-in-the-loop approval workflows
- Long-running agent processes with persistence
- Branching and cyclical agent logic
Similar Tools
When to Use
Best for: Complex multi-agent workflows needing durable execution and fine-grained control
Avoid when: Simple single-agent use cases or when LangChain dependency is unwanted
Original data from HuggingFace, OpenCompass and various public git repos.
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Release v20260324