Agno

Agno (formerly Phidata) is a full-stack platform for production multi-agent systems, built by former Airbnb engineers with 40K+ GitHub stars. It covers the complete path from local development to production deployment — a three-in-one stack of SDK for building, the AgentOS runtime, and a visual control plane — with your first agent live in 20 lines of Python.

Core Capabilities

• Extreme performance: Agent instantiation takes only 3μs — 529x faster than LangGraph — supporting high-concurrency scenarios
• Full-stack architecture: SDK + AgentOS + Control Plane in three integrated layers, covering the entire path from development to production
• Privacy-first: All data stays in the user's own cloud, with built-in JWT, RBAC, and multi-tenant isolation
• Knowledge base integration: Built-in RAG, vector storage, and 100+ toolkits, ready out of the box for knowledge-intensive scenarios
• Multi-model support: Compatible with 30+ providers, including OpenAI, Claude, and Gemini
• Production-grade API: AgentOS provides 50+ REST endpoints, SSE/WebSocket, and session management

Use Cases The first choice for Python developers building production-grade agent systems. Best for knowledge-intensive applications (legal research, financial analysis, enterprise knowledge base Q&A) and enterprise customers with strict data privacy requirements. Non-developers or scenarios that need fine-grained state machines should consider other options.

Unique Advantages The only choice among the four major frameworks that offers a complete Control Plane — not just a code library, but an end-to-end platform. Its 529x instantiation speed makes it a natural fit for high concurrency, whereas the LangChain ecosystem requires far more self-built infrastructure to reach the same production readiness.

Editor's Review Recommendation index 4/5. Developer feedback includes "abandoned LangGraph and switched fully to Agno — everything is more logical." You can start with the free open-source SDK, and the Pro plan unlocks the production control console. One caution: the v2.0 upgrade drew community complaints, so new projects should pin versions before going live.