Agno
Model-agnostic, async-first Python agent framework with built-in team orchestration, multimodal support, memory, and persistent storage — the official successor to Phidata.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
LLM API keys are passed via environment variables or constructor arguments; no credential vault integration out of the box. Tool sandboxing is the developer's responsibility.
⚡ Reliability
Best When
You want a batteries-included, async-native Python agent framework with team orchestration and built-in storage that works across OpenAI, Anthropic, Google, and open-source models.
Avoid When
You need fine-grained graph control flow or are already deeply invested in LangGraph's ecosystem and do not want to switch paradigms.
Use Cases
- • Multimodal agents that process images, audio, and text in a single unified Agent with model-agnostic backends
- • Team-based workflows where a Team orchestrator routes tasks to specialized sub-agents based on role descriptions
- • Async-first production agents that handle concurrent tool calls and multiple user sessions without blocking
- • Agents with built-in long-term memory using AgentMemory backed by PostgreSQL or SQLite for session continuity
- • Knowledge-base-augmented research agents that embed documents into vector stores and retrieve context at inference time
Not For
- • Teams requiring graph-based control flow with explicit conditional edges and cycle detection
- • Environments where Python is not available or where a REST API agent server is needed out of the box
- • Projects that need automatic prompt optimization — use DSPy for optimizer-driven prompt tuning
Interface
Authentication
Library — auth handled by underlying LLM provider. Agno cloud platform features require a separate API key.
Pricing
Mozilla Public License 2.0. Formerly Phidata — migration guide available in official docs.
Agent Metadata
Known Gotchas
- ⚠ Agno is the renamed successor to Phidata — import paths changed from 'phi' to 'agno' and old phidata code requires migration before using the new package
- ⚠ Team mode with mode='coordinate' requires the lead model to be capable of following complex delegation instructions — weaker models silently fail to route correctly
- ⚠ Async agents using async tools require the entire call chain to be async; mixing sync and async tool functions causes event loop blocking
- ⚠ Built-in memory requires explicit storage backend configuration (SQLite or PostgreSQL); the default in-memory storage does not persist across process restarts
- ⚠ Model-agnostic abstraction occasionally lags behind provider SDK updates — newly released model features may not be exposed until Agno adds explicit support
Alternatives
Full Evaluation Report
Detailed scoring breakdown, competitive positioning, security analysis, and improvement recommendations for Agno.
Scores are editorial opinions as of 2026-03-06.