LangGraph vs CrewAI
A side-by-side view of two listings from the BuildStack.ai AI agent harnesses directory, for software vendors and family-office technology buyers. Every value is copied from the listing data, verified (Asia/Singapore) from the sources linked below.
Summary
LangGraph and CrewAI are both listed in AI agent harnesses. Of the 5 capabilities compared there, both document 5: Multi-agent, Durable state / resume, Human-in-the-loop, Tracing / observability, MCP support.
Their capability marks are identical, so the differences are in languages, license, hosting and the vendor notes shown in the table below.
Best fit, as stated in each listing — LangGraph: Teams that want explicit, graph-level control over long-running stateful agents and may later want a managed deployment runtime. CrewAI: Teams prototyping role-based multi-agent automations in Python who may want a vendor-run control plane later.
Side-by-side comparison
✔ = documented by the vendor · ✕ = not offered / vendor says no · ? = not verified. Values are shown exactly as stored in the listing.
| Field | LangGraph | CrewAI |
|---|---|---|
| Website | https://www.langchain.com/langgraph | https://www.crewai.com |
| Type | Open source + managed | Open source + managed |
| Languages / SDKs | Python, JavaScript/TypeScript (LangGraph.js) | Python |
| License | MIT | MIT |
| Hosting model | Self-hosted library; LangSmith Deployment (Cloud, BYOC or self-hosted) for managed runtime | Self-hosted open-source framework; CrewAI AMP Suite for managed deployment, observability and governance |
| GitHub ★ | langchain-ai/langgraph · ★ 43,523 (as of 2026-10-20) — Python repo; LangGraph.js is a separate repo. | crewAIInc/crewAI · ★ 59,879 (as of 2026-10-20) |
| Multi-agent | ✔ | ✔ |
| Durable state / resume | ✔ | ✔ |
| Human-in-the-loop | ✔ | ✔ |
| Tracing / observability | ✔ | ✔ |
| MCP support | ✔ | ✔ |
| Description | Low-level orchestration framework from LangChain for building, managing and deploying long-running, stateful agents as graphs. | Python framework for multi-agent automation: Crews of role-based agents plus event-driven Flows, with CrewAI AMP as the commercial control plane. |
| Best fit | Teams that want explicit, graph-level control over long-running stateful agents and may later want a managed deployment runtime. | Teams prototyping role-based multi-agent automations in Python who may want a vendor-run control plane later. |
| Details | Durable execution that resumes from where a run left off; human-in-the-loop via interrupts; short- and long-term memory; tracing and evals through LangSmith (separate product); MCP via LangChain's MCP adapter (langchain[mcp]); documented multi-agent patterns (subagents, handoffs, router). | Crews (autonomous agent teams) and Flows (event-driven workflows with managed state); checkpointing and async execution; human input / human-in-the-loop workflows; tracing and observability; MCP servers as tools and A2A support. |
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Sources
LangGraph sources
CrewAI sources
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