Build powerful agents with ease_

Agno is an open-source Python framework for building and running AI agents. It provides ready-made components—like LLM interfaces, memory, knowledge retrieval, and tool integrations—so developers can focus on logic and features instead of infrastructure.

Agno’s modular design allows you to swap LLMs, databases, or vector stores without rewriting code, and its built-in state management, observability, and human-in-the-loop capabilities make it easier to deploy stable, production-grade agents.

Agno is written in Python, the most widely used language for AI development. It works seamlessly with common Python environments, package managers, and popular data science tooling.

Yes. Agno supports plug-and-play LLM integrations, including OpenAI GPT, Anthropic Claude, Google Gemini, and open-source models (e.g., LLaMA, Mistral) through Ollama or other providers. Switching models requires no core-logic rewrite.

Absolutely. Agno allows you to compose multiple agents that can plan, communicate, and delegate tasks to one another. This enables complex, multi-step workflows such as research pipelines, automated data processing, or customer-support triage.

Agno includes built-in session management to keep conversations and user memory consistent across interactions and scale to many concurrent sessions. It also offers flexible memory primitives—from short-term context to long-term user learning storage—so agents can remember key facts and maintain continuity over time.

Yes. Agno supports human-in-the-loop flows like User Confirmation, User Input, and External Tool Execution. This ensures that humans can review, correct, or guide critical decisions, maintaining accuracy and safety.

Agno provides day-zero, single-line integrations with major vector databases (Pinecone, Weaviate, Qdrant), cloud storage (AWS S3, GCP), collaboration tools (Slack, Notion), and more. Support for the Model Context Protocol (MCP) lets agents securely connect to live data sources and trigger workflows with minimal configuration.

Yes. Agno is built for production-grade reliability with built-in error handling, retries, observability (logging and monitoring), and state persistence. It supports FastAPI integration and runs on containerized infrastructure like Docker or Kubernetes, and can scale from a single agent to thousands of concurrent sessions.