Build, run, manage multi-agent systems.

Agno is a framework, runtime, and control plane for multi-agent systems.

• Private by design. AgentOS runs in your cloud. The control plane connects directly to your runtime from your browser. No retention costs, no vendor lock-in, no compliance headaches.
• Production-ready on day one. Pre-built FastAPI runtime with SSE endpoints, ready to deploy.
• Fast. 529× faster instantiation than LangGraph. 24× lower memory. See benchmarks →

An agent with MCP tools, persistent state, served via FastAPI:

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.anthropic import Claude
from agno.os import AgentOS
from agno.tools.mcp import MCPTools

agno_agent = Agent(
    name="Agno Agent",
    model=Claude(id="claude-sonnet-4-5"),
    db=SqliteDb(db_file="agno.db"),
    tools=[MCPTools(transport="streamable-http", url="https://docs.agno.com/mcp")],
    add_history_to_context=True,
    markdown=True,
)

agent_os = AgentOS(agents=[agno_agent])
app = agent_os.get_app()

if __name__ == "__main__":
    agent_os.serve(app="agno_agent:app", reload=True)

Run this and connect to the AgentOS UI:

Core

• Model-agnostic: OpenAI, Anthropic, Google, local models
• Type-safe I/O with input_schema and output_schema
• Async-first, built for long-running tasks
• Natively multimodal (text, images, audio, video, files)

Memory & Knowledge

• Persistent storage for session history and state
• User memory across sessions
• Agentic RAG with 20+ vector stores, hybrid search, reranking
• Culture: shared long-term memory across agents

Orchestration

• Human-in-the-loop (confirmations, approvals, overrides)
• Guardrails for validation and security
• Pre/post hooks for the agent lifecycle
• First-class MCP and A2A support
• 100+ built-in toolkits

Production

• Ready-to-use FastAPI runtime
• Integrated control plane UI
• Evals for accuracy, performance, latency
• Durable execution for resumable workflows
• RBAC and per-agent permissions

1. Follow the getting started guide
2. Browse the cookbook for real-world examples
3. Read the docs to go deeper

Agent workloads spawn hundreds of instances. Stateless, horizontal scalability isn't optional.

_{Apple M4 MacBook Pro, Oct 2025. Run benchmarks yourself →}

Add our docs to your AI-enabled editor:

Cursor: Settings → Indexing & Docs → Add https://docs.agno.com/llms-full.txt

Also works with VSCode, Windsurf, and similar tools.

We welcome contributions. See the contributing guide.

Agno logs which model providers are used to prioritize updates. Disable with AGNO_TELEMETRY=false.

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