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High-performance Python agent framework designed for multi-agent systems and production workloads with microsecond agent instantiation.
High-performance Python agent framework designed for multi-agent systems and production workloads with microsecond agent instantiation.
Agno (formerly Phidata) is a Python-native framework for building agents, teams of agents, and agentic workflows that are fast enough to run in production. Its selling point is raw performance — Agno benchmarks agent instantiation in microseconds and memory footprint in kilobytes, so you can spin up thousands of specialized agents per request instead of one bloated do-everything agent. The framework provides five building blocks: Agents (single-purpose with tools), Teams (coordinated multi-agent groups), Workflows (deterministic multi-step pipelines), Memory (session and long-term), and Knowledge (RAG over any source). It supports 20+ LLM providers, 40+ vector databases, and hundreds of pre-built tools including web search, SQL, filesystem, and MCP integrations. Agno also ships AgentOS, a self-hosted runtime with a monitoring dashboard, so teams can deploy and observe their agents on their own infrastructure without vendor lock-in. The framework is open source under MPL-2.0 and used at production scale by companies building customer support, financial analysis, and internal RAG copilots. Documentation is excellent, examples are copy-runnable, and the community on Discord is responsive. There's no hosted service — you run it yourself — which makes it a great fit for teams that want to keep their agent stack private.
Agno (formerly Phidata) bundles agent memory, knowledge bases, tools, and multi-agent orchestration into a single Python framework. Faster and simpler than LangChain for most agent use cases, with a production runtime (AgentOS) for teams that need managed hosting. The open-source tier covers most needs.
Free
$150/month
Custom
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As of 2026, Agno is being marketed around the pairing of its open-source Python framework with AgentOS, positioned as the first enterprise-ready agentic operating system. The emphasis is on production readiness: fast agent instantiation, low memory overhead, scalable runtime behavior, and private-by-default deployment inside the customer's own cloud. The product is accumulating significant community signal, with the site citing 36,000+ aggregate ratings, reflecting growing adoption as teams move agent projects from prototype to production in 2026.
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