CrewAI
Multi-agent automation framework & studio to build and run AI crews
Open-Source Projects
Discover top open-source software, updated regularly with real-world adoption signals.
Discover top open-source software, updated regularly with real-world adoption signals.
Fast, private, scalable framework for building multi-agent AI systems
Agno delivers a high-performance Python framework, FastAPI runtime, and UI control plane for creating agents, teams, and step-based workflows with built-in privacy, toolkits, and model-agnostic support.
Agno is a Python‑first framework that lets developers define agents, multi‑agent teams, and deterministic step‑based workflows. It abstracts persistence, memory, knowledge retrieval, and dynamic context, while remaining model‑agnostic and type‑safe.
The bundled AgentOS runtime ships a pre‑configured FastAPI app with SSE‑compatible endpoints, enabling day‑one deployment. An integrated UI control plane provides real‑time monitoring, debugging, and human‑in‑the‑loop interactions. All components run in your own cloud environment, guaranteeing data never leaves your infrastructure and supporting role‑based access control.
Agno includes over 100 built‑in toolkits, multimodal support (text, images, audio, video, files), and first‑class Model Context Protocol (MCP) integration. Developers can plug in any LLM provider, connect to 20+ vector stores for RAG, and enforce guardrails through schema validation and lifecycle hooks.
When teams consider Agno, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Personalized Customer Support Bot
Provides consistent, context‑aware assistance across sessions using persistent user memory.
Research Assistant with Human‑in‑the‑Loop
Generates accurate reports by combining vector‑store retrieval, RAG, and manual validation steps.
Automated Data Pipeline
Orchestrates ingestion, transformation, and visualization agents to deliver end‑to‑end data processing.
Enterprise Compliance Monitoring
Runs a team of agents with guardrails and RBAC to audit policies while keeping all data private.
Agno is a Python framework; agents, teams, and workflows are defined in Python.
Yes, Agno is model‑agnostic and works with any provider that offers an API compatible with its model interface.
All runtime components run in your own cloud or on‑premise environment; no data is sent to external services, and RBAC controls access.
MCP (Model Context Protocol) enables agents to exchange structured context with external systems; Agno provides first‑class MCP integration.
The FastAPI runtime can be horizontally scaled behind a load balancer, and agents can share persistent storage to maintain state across instances.
Project at a glance
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