Agno vs LangGraph: agent frameworks compared

Agno and LangGraph solve different layers. Per their docs, Agno provides a service layer that runs agents behind a REST API and MCP server, while LangGraph is an orchestration runtime for durable, stateful agent graphs. Choose by whether you need hosting or graph control. Checked 2026-10-14.

Quick comparison

The order below is editorial and reflects how directly each tool's documentation matches the query, not a verdict on quality.

How the options differ

What each one is for

Agno's docs say it helps companies run agents as a service, and describe it as the orchestration and service layer around your agents. The repository describes itself as "Build, run, and manage agent platforms." (GitHub).

LangGraph's docs call it the orchestration runtime, with durable execution, streaming, human-in-the-loop and persistence. Its repository description is "Build resilient agents." (GitHub).

How you build agents

Agno's docs say you can build agents with the Agno SDK, Claude Agent SDK, Codex SDK, or another supported framework, then run them through AgentOS.

LangGraph's overview shows a graph-based API: a StateGraph with nodes and edges that is compiled and invoked. It also says you can mix deterministic and agentic steps in a single graph.

Deployment and surfaces

Agno's docs list a REST API for your product, an MCP server for Claude and ChatGPT, and Interfaces for Slack, WhatsApp and Telegram. They also describe an AgentOS UI for monitoring runs and inspecting sessions, and deployment starter repositories for Railway, Docker, AWS, Fly, GCP, Helm, Azure, Render and Modal.

LangGraph's overview mentions production-ready deployment for stateful, long-running workflows and debugging with LangSmith. LangSmith is described as the platform for tracing, evaluation, prompts and deployment across frameworks.

License and age

Agno's repository reports Apache-2.0 and was created on 2022-05-04. LangGraph's repository reports MIT and was created on 2023-08-09. Both licenses apply to the repository code; neither is a statement about hosted service pricing.

For recent releases, see Agno v3.1.3 and LangGraph 1.2.15.

Agno vs LangGraph vs LangChain

The LangGraph overview positions LangChain as the agent framework: abstractions and integrations for models, tools and agent loops. LangGraph sits beneath it as the orchestration runtime, and Deep Agents is described as a harness built on top of LangGraph.

That means "LangGraph vs LangChain" is a question about layers within one product family, according to the overview. Agno's sources do not mention LangChain, and the LangChain material cited here is limited to that overview page, so no further LangChain-specific comparison is made. LangChain has no separate item in this guide.

How we compared

We read four primary sources: the GitHub repository metadata and the documentation or overview pages for both Agno and LangGraph. All were checked on 2026-10-14. We compared descriptions, licenses, creation dates, documented surfaces and deployment claims.

We did not install or run either tool, did not benchmark them, and did not verify any documented capability in practice. Nothing here is hands-on testing.

Limitations

The cited sources do not state pricing for either tool, including any hosted offering such as LangSmith deployment or an Agno control plane. They give no performance figures, adoption numbers or star counts.

They do not compare the two tools directly, and they do not say how Agno and LangGraph might be used together. Model provider support and language support beyond what is quoted are not stated in the cited sources.

Browse more options in Frameworks or see the Mastra hub as an alternative. Related launches: Agno v3.1.3 and the Agno and LangGraph hubs.