LangGraph Agent

v1.0

LangChain

Agentworkflowlangchainopen-source
82
Strong
About This Agent

LangChain's graph-based agent framework for building stateful, multi-actor applications with cycles and controllable execution flow. Enables complex, cyclic agent workflows with human-in-the-loop capabilities.

Last Evaluated: November 9, 2025
Official Website

Trust Vector Analysis

Dimension Breakdown

🚀Performance & Reliability
+
task completion accuracy

Based on underlying model performance and framework overhead

Evidence
LangGraph Documentation — Supports multiple LLM providers with consistent performance
highVerified: 2025-11-09
tool use reliability

Tool integration testing

Evidence
LangGraph Tools — Native integration with LangChain tools ecosystem
highVerified: 2025-11-09
multi step planning

Complex task testing with graph execution

Evidence
LangGraph Cycles — Explicit graph structure enables sophisticated multi-step workflows with cycles
highVerified: 2025-11-09
memory persistence

Memory persistence testing

Evidence
LangGraph Checkpointing — Built-in checkpointing with multiple backend support (SQLite, PostgreSQL, Redis)
highVerified: 2025-11-09
error recovery

Error handling testing

Evidence
LangGraph Error Handling — Supports custom error handling and retry logic in graph nodes
mediumVerified: 2025-11-09
latency

Performance monitoring

Evidence
Community Benchmarks — Latency depends on graph complexity and LLM provider
mediumVerified: 2025-11-09
🛡️Security
+
tool sandboxing

Security architecture review

Evidence
LangGraph Documentation — Tool sandboxing depends on implementation, not enforced by framework
mediumVerified: 2025-11-09
access control

Access control capabilities assessment

Evidence
LangGraph Self-Hosted — Access control implementation is developer's responsibility
mediumVerified: 2025-11-09
prompt injection defense

Injection attack testing

Evidence
LangChain Security — Provides guidance but requires developer implementation
mediumVerified: 2025-11-09
data isolation

Data architecture review

Evidence
LangGraph Persistence — Thread-based isolation when using proper checkpointing
highVerified: 2025-11-09
open source transparency

Source code review

Evidence
LangGraph GitHub — Fully open source with MIT license, code auditable
highVerified: 2025-11-09
🔒Privacy & Compliance
+
data retention

Privacy policy review

Evidence
Self-Hosted Architecture — Full control over data retention when self-hosted
highVerified: 2025-11-09
gdpr compliance

Compliance capabilities assessment

Evidence
Open Source Framework — GDPR compliance depends on deployment configuration
mediumVerified: 2025-11-09
third party data sharing

Data flow analysis

Evidence
LLM Provider Integration — Data shared with chosen LLM provider (OpenAI, Anthropic, etc.)
mediumVerified: 2025-11-09
local deployment option

Deployment options assessment

Evidence
LangGraph Deployment — Fully supports local deployment with local LLMs
highVerified: 2025-11-09
👁️Trust & Transparency
+
documentation quality

Documentation completeness review

Evidence
LangGraph Docs — Comprehensive documentation with tutorials and examples
highVerified: 2025-11-09
execution traceability

Logging capabilities assessment

Evidence
LangSmith Integration — Excellent tracing via LangSmith integration, shows full graph execution
highVerified: 2025-11-09
decision explainability

Explainability features assessment

Evidence
Graph Visualization — Graph structure provides clear execution flow visualization
mediumVerified: 2025-11-09
open source code

Open source assessment

Evidence
GitHub Repository — MIT licensed, 5k+ stars, active development
highVerified: 2025-11-09
⚙️Operational Excellence
+
ease of integration

Integration complexity assessment

Evidence
LangGraph Quickstart — Requires understanding of graph concepts, steeper learning curve
mediumVerified: 2025-11-09
scalability

Scalability testing

Evidence
LangGraph Cloud — Supports horizontal scaling with proper infrastructure
highVerified: 2025-11-09
cost predictability

Pricing model analysis

Evidence
Open Source Pricing — Free framework, costs only from LLM API usage
highVerified: 2025-11-09
monitoring capabilities

Monitoring features assessment

Evidence
LangSmith — Excellent monitoring via LangSmith platform
highVerified: 2025-11-09
community support

Community activity analysis

Evidence
GitHub Discussions — Growing community but newer framework
mediumVerified: 2025-11-09
Strengths
  • +Full control over agent execution flow with explicit graph structure
  • +Excellent for complex, cyclic workflows with human-in-the-loop
  • +Open source with MIT license, fully auditable code
  • +Built-in checkpointing and state persistence
  • +Strong integration with LangChain ecosystem and tools
  • +Superior observability via LangSmith integration
Limitations
  • !Steeper learning curve compared to simpler agent frameworks
  • !Requires more code for simple use cases
  • !Security and sandboxing must be implemented by developer
  • !Relatively newer framework with evolving APIs
  • !Performance overhead from graph execution layer
  • !Limited managed service options (LangGraph Cloud in beta)
Metadata
license: MIT
supported models
0: Any LangChain-compatible model
1: OpenAI
2: Anthropic
3: Local LLMs
programming languages
0: Python
1: JavaScript/TypeScript
deployment type: Self-hosted or LangGraph Cloud
tool support
0: LangChain tools
1: Custom tools
2: Function calling
github stars: 11700+
monthly downloads: 7M+ on PyPI
first release: 2024
pricing: Free (MIT license) - Cloud deployment via LangSmith Plus/Enterprise plans
ga version: 1.0 (October 2025)

Use Case Ratings

customer support

Excellent for complex support workflows with human-in-the-loop

code generation

Good for multi-step code generation with review cycles

research assistant

Graph structure ideal for complex research workflows

data analysis

Works well but requires custom tool integration

content creation

Good for iterative content workflows with review stages

education

Graph-based curriculum paths work well for tutoring

healthcare

Requires careful security implementation for healthcare data

financial analysis

Self-hosted option good for compliance, needs security hardening

legal compliance

Multi-stage review workflows map well to graph structure

creative writing

Cyclic graph structure excellent for iterative ideation