Agno
ActiveOverview
Agno is a platform for building, running, and managing AI agent platforms. It consists of a 3-layer architecture: SDK for building agents, multi-agent teams, and workflows; Runtime for running them as production services with session management, tracing, and RBAC; and Control Plane for platform management via AgentOS UI. Everything except the Control Plane is free and open-source. It targets developers creating production AI agent systems, supporting multimodal agents with memory, knowledge, tools, and reasoning.
Key Features
- Production API - 50+ endpoints with SSE and websockets for building products on agent platforms.
- Storage - Postgres for sessions/memory, Clickhouse for traces.
- 100+ Integrations - Pre-built toolkits for integrating with external tools.
- Context Providers - Access live data from Slack, Drive, wikis, MCP, and custom sources.
- Observability - OpenTelemetry tracing, run history, and audit logs.
- Security - JWT-based RBAC and multi-tenant isolation.
- Interfaces - Expose agents via Slack, Telegram, WhatsApp, Discord, AG-UI, A2A.
- Scheduling - Cron-based scheduling and background jobs.
- User Profiles - Structured storage for user static facts and dynamic context.
Pricing
| Plan | Price | Includes |
|---|---|---|
| Free Tier | Free | SDK, Runtime, open-source components, self-hosted storage. |
| Control Plane | Paid (usage-based) | AgentOS UI for managing platforms, hosted control plane. |
| Enterprise | Custom | Advanced RBAC, support, custom deployments. |
Platforms & Requirements
Deploys as containerized images on any cloud platform supporting Docker. Requires Postgres for operational data and optionally Clickhouse for traces. No specific hardware minimums stated; performance optimized for low memory footprint.
Integrations & Ecosystem
- Supermemory (memory API)
- Tavily (web search)
- OpenAI models
- Slack, Telegram, WhatsApp, Discord
- Postgres, Clickhouse
- OpenTelemetry
- 100+ toolkits for databases/APIs
Alternatives
| App | Difference |
|---|---|
| LangChain | More modular LLM chaining library; less focus on production runtime and control plane. |
| CrewAI | Emphasizes multi-agent collaboration; lighter on production deployment features. |
| AutoGen | Microsoft-backed conversational agents; requires more custom orchestration. |
| Haystack | Specialized in RAG pipelines; narrower scope than full agent platforms. |
Reputation
Agno is recognized for its speed, low memory footprint, and model-agnostic design, making it suitable for production multi-agent systems. Users praise the simple Python-based setup and extensive integrations. Some note it's relatively new (released 2023), with community growth ongoing but smaller than established frameworks.
Sources (7)
- https://supermemory.ai/docs/integrations/agno
- https://docs.agno.com/examples/learning/user-profile/overview
- https://docs.agno.com
- https://www.digitalocean.com/community/conceptual-articles/agno-fast-scalable-multi-agent-framework
- https://www.youtube.com/watch?v=XN6dSSx6Ehg
- https://docs.agno.com/learning/stores/user-profile
- https://docs.tavily.com/documentation/integrations/agno