LangGraph Enterprise SDK
An enterprise-grade Agent Platform SDK inspired by LangGraph, built with TOON & ZAD principles, designed for governance, security, scalability, and multi-agent systems.
🚀 Overview
LangGraph Enterprise SDK is a production-ready Agent Platform SDK that provides a governed, secure, and extensible foundation for building single-agent and multi-agent systems in enterprise and regulated environments.
This SDK does not replace LangGraph.
Instead, it hardens and operationalizes agent execution, adding the layers required for real-world production use.
🎯 Why This SDK Exists
Most agent frameworks are optimized for:
- Prototyping
- Demos
- Experiments
They are not sufficient for:
- Governance & compliance
- Multi-tenant isolation
- Long-running agents
- Human-in-the-loop workflows
- Deterministic replay & audit
- Security boundaries
- Enterprise DevOps & SRE operations
This SDK fills that gap.
🧠 Core Design Principles
1️⃣ TOON – Tool-Oriented Orchestration Nodes
- Nodes only orchestrate
- Tools perform side effects
- LLMs perform reasoning
- Clear separation of responsibilities
2️⃣ ZAD – Zero-Action Design
- No implicit state mutation
- No hidden side effects
- Deterministic execution
- Replayable workflows
3️⃣ Enterprise-First Architecture
- Security & governance are first-class
- Observability is built-in
- Persistence & recovery are mandatory
- Protocols (A2A, MCP) are standards-based
🧩 High-Level Architecture
Client / UI
|
Server (Control Plane)
(Auth, Tenancy, Lifecycle)
|
Execution Runtime
(GraphExecutor, Scheduler)
|
Workflows
(Planner, Supervisor)
|
Nodes (TOON)
|
LLMs (Reasoning) ---- Tools (Side Effects)
📦 Key Capabilities
✅ Agent Execution
- Deterministic graph execution
- Retry & cancellation support
- Lifecycle hooks
- Streaming events
✅ Multi-Agent Workflows
- Planner / Supervisor model
- Explicit delegation
- A2A-ready design
✅ Governance
- Approval workflows
- Audit logging
- Compliance policies
- Quotas & rate limits
✅ Security
- Authentication & Authorization
- RBAC
- Tenant & execution isolation
- Secrets abstraction
✅ Persistence & Durability
- Checkpointing
- Snapshots (time-travel)
- Crash recovery
- Replay & resume
✅ Memory & RAG
- Postgres / Redis memory
- pgvector / OpenSearch vector stores
- Embedding abstraction
✅ Knowledge Graph
- Neo4j integration
- SOP / Runbook reasoning
- Dependency & impact analysis
✅ LLM Abstraction
- OpenAI
- Azure OpenAI
- Anthropic
- Ollama
- LLaMA-cpp
- Groq
- Custom / on-prem models
✅ MCP (Model Context Protocol)
- Tool invocation via protocol
- HTTP / stdio / WebSocket
- Secure metadata propagation
✅ Observability
- Structured logging
- Metrics (Prometheus)
- Tracing (OpenTelemetry)
- Dashboard registry
📁 Project Structure
src/
├── api/
├── execution/
├── workflows/
├── tools/
├── llm/
├── memory/
├── graph_store/
├── mcp/
├── a2a/
├── governance/
├── security/
├── persistence/
├── streaming/
├── observability/
├── server/
├── utils/
└── connectors/
⚙️ Installation
Core SDK
pip install langgraph-enterprise-sdk
Full Enterprise Install
pip install "langgraph-enterprise-sdk[enterprise]"
LLM Providers
pip install "langgraph-enterprise-sdk[all-llms]"
🧪 Testing
Enterprise-grade test strategy:
tests/
├── unit/
├── integration/
├── security/
├── durability/
└── load/
Run all tests:
pytest
🔐 Security Model
- Zero-trust by default
- AuthN → AuthZ → Policy → Isolation → Execution
- Tools are sandboxed
- No implicit privilege escalation
- Multi-tenant safe
🔄 Relation to LangGraph
| LangGraph | This SDK |
|---|---|
| Graph execution | Deterministic runtime |
| Nodes | TOON-compliant nodes |
| State | Immutable ZAD state |
| Memory | Enterprise memory + RAG |
| Tools | Sandboxed & governed |
| Agents | Multi-agent workflows |
| Server | Control plane |
| Governance | Built-in |
LangGraph can be used inside this SDK but is not exposed directly to application teams.
🏢 Who Should Use This?
✔ Platform Engineering Teams
✔ Enterprise AI / GenAI Teams
✔ Regulated Industries (Banking, Healthcare, Telecom)
✔ DevSecOps & SRE Teams
✔ Organizations building agent platforms, not just agents
🤝 Contributing
See CONTRIBUTING.md
📜 License
Apache 2.0 — see LICENSE
🏁 Final Note
This repository is not a demo.
It is a platform-grade foundation for building safe, scalable, enterprise AI agents.
Metadata
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Total release size: 121.0 kB
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