A side-by-side of two agent frameworks for building AI agents — live GitHub data, languages, and what each is best at.
Short answer: Agno leads Agno vs LangGraph by community traction (★ 42k vs ★ 39k). Pick Agno for full-stack agents; pick LangGraph for stateful multi-agent workflows.
✓ Live data verified
| Agno | LangGraph | |
|---|---|---|
| GitHub stars | ★ 42k | ★ 39k |
| Language | Python | Python |
| Category | Agent frameworks | Agent frameworks |
| Best for | full-stack agents | stateful multi-agent workflows |
| Repository | agno-agi/agno | langchain-ai/langgraph |
Agno and LangGraph are both credible choices. By community traction, Agno leads (★ 42k). Pick Agno for full-stack agents; pick LangGraph for stateful multi-agent workflows.
Both are credible agent frameworks. By community traction Agno leads (★ 42k). Pick Agno for full-stack agents; pick LangGraph for stateful multi-agent workflows.
Agno is Batteries-included agent runtime — built-in memory, knowledge/RAG, and AgentOS, a control plane you run in your own cloud. Formerly Phidata.. LangGraph is Graph-based orchestration for stateful, multi-actor agent workflows with explicit control flow and checkpointing..
Agno has more — ★ 42k vs ★ 39k (live counts).
Often yes — many teams combine agent frameworks. Check each tool's docs for interop; they solve overlapping but not identical problems.
Agno is primarily Python; LangGraph is primarily Python.
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