CrewAI
Multi-agent automation framework & studio to build and run AI crews
Agno
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.
Overview
Overview
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.
Production Ready
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.
Extensibility
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.
Highlights
FastAPI‑ready runtime with SSE endpoints for production
Integrated UI control plane for real‑time monitoring and debugging
Model‑agnostic, type‑safe agent definitions with schema enforcement
Private‑by‑design deployment with RBAC and on‑premise data storage
Pros
- High performance and horizontal scalability
- End‑to‑end production stack (runtime + UI) out of the box
- Strong privacy guarantees; no data leaves your cloud
- Extensive built‑in toolkits and multimodal capabilities
Considerations
- Requires Python and FastAPI expertise to get started
- Self‑hosting infrastructure is needed for production use
- Steep learning curve for advanced workflow features
- Community ecosystem is still maturing compared to larger frameworks
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Fit guide
Great for
- Enterprises that must keep data on‑premise or in a private cloud
- Teams building complex multi‑agent workflows with shared state
- Developers needing a ready‑made FastAPI deployment for AI products
- Projects that require strict access control, auditability, and guardrails
Not ideal when
- Simple single‑agent prototypes with minimal resource requirements
- Non‑Python environments or teams without FastAPI experience
- Users preferring no‑code AI platforms or managed cloud services
- Use cases that need an out‑of‑the‑box hosted solution
How teams use it
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.
Tech snapshot
Python100%
Shell1%
Batchfile1%
Frequently asked questions
Which programming languages does Agno support?
Agno is a Python framework; agents, teams, and workflows are defined in Python.
Can I use any LLM provider with Agno?
Yes, Agno is model‑agnostic and works with any provider that offers an API compatible with its model interface.
How is data privacy ensured?
All runtime components run in your own cloud or on‑premise environment; no data is sent to external services, and RBAC controls access.
What is MCP and why does it matter?
MCP (Model Context Protocol) enables agents to exchange structured context with external systems; Agno provides first‑class MCP integration.
How does Agno scale for large deployments?
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
Active- Stars
- 37,072
- Watchers
- 37,072
- Forks
- 4,914
LicenseApache-2.0
Repo age3 years old
Last commit1 hour ago
Primary languagePython
Last synced 54 minutes ago