agno

Build and deploy multi-agent systems with an integrated AgentOS runtime.

15|2|Updated Nov 17, 2025
One-click install
npx skills add https://github.com/OutlineDriven/odin-codex-plugin --skill agno-outlinedriven
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: agno
Source: https://github.com/OutlineDriven/odin-codex-plugin/tree/main/skills/agno
Command: npx skills add https://github.com/OutlineDriven/odin-codex-plugin --skill agno-outlinedriven

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Agno provides a production-grade framework to design, deploy, and manage multi-agent systems with a fast AgentOS runtime and built-in MCP support, enabling secure, on-premises operation.

Core Features & Use Cases

  • AgentOS runtime for hosting Agents, Teams, and Workflows with streaming capabilities
  • MCP integration for stdio, SSE, and Streamable HTTP transports to connect to external systems
  • Memory, knowledge bases, and persistence for long-running conversations and data-driven tasks
  • Modular toolkits and extensible tooling for data, code, and enterprise integrations
  • Use cases include building customer-support agents, knowledge-enabled workflows, and automated enterprise processes

Quick Start

Create a minimal Agent with a model, wrap it in AgentOS, and run it locally.

Frequently Asked Questions about agno

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I orchestrate multi-agent workflows with memory and knowledge bases?

You orchestrate multi-agent workflows by using an AgentOS runtime to host agents, teams, and workflows with integrated memory, knowledge bases, and persistence for long-running conversations and data-driven tasks.

What is an AgentOS runtime for hosting AI agents?

An AgentOS runtime is a production-grade framework environment for designing, deploying, and managing multi-agent systems with streaming capabilities, built-in MCP support, and secure on-premises operation.

Can I connect AI agents to external systems using MCP transports?

Yes, you can connect AI agents to external systems using MCP integration, which supports stdio, SSE, and Streamable HTTP transports for secure, on-premises enterprise integrations.

Does this multi-agent framework support human-in-the-loop processes?

Yes, the framework supports human-in-the-loop processes, enabling production-ready AI agents and teams to handle scenarios requiring manual intervention alongside automated enterprise workflows.

What's the best way to deploy multi-agent systems in on-premises environments?

The best way to deploy multi-agent systems on-premises is using modular tooling with robust guards and multiple transport supports like stdio, SSE, and Streamable HTTP within an AgentOS runtime.