agno
CommunityAutomate multi-agent AI systems with MCP and memory.
System Documentation
What problem does it solve?
Agno provides a modern framework for building production-ready multi-agent systems, including an AgentOS runtime, MCP server integration, workflow orchestration, and memory/knowledge management. It reduces the complexity of designing, deploying, and debugging agent-powered applications by offering a cohesive architecture that combines agents, teams, and workflows with telemetry and scalable transports.
Core Features & Use Cases
- AgentOS runtime with MCP integration (stdio, SSE, Streamable HTTP)
- Memory and knowledge capabilities (session memory, RAG knowledge bases, user memories)
- Multi-agent teams and role-based delegation with orchestration patterns
- Workflows with conditional branching, loops, and async execution
- Production-ready API integrations (FastAPI apps, JWT middleware, databases)
- Debugging, telemetry, and performance optimization features
Quick Start
Build a basic multi-agent setup by combining an Agent with a couple of Tools, then orchestrate a small Workflow to demonstrate memory, knowledge, and tool usage.
Dependency Matrix
Required Modules
None requiredComponents
💻 Claude Code Installation
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Please help me install this Skill: Name: agno Download link: https://github.com/delorenj/skills/archive/main.zip#agno Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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