Agno
Provide an SDK and runtime for building agent platforms — role-defined Agents, multi-mode Teams (coordinate / route / broadcast / sequential), Workflows, persistent memory/storage/knowledge, MCP toolkits, and AgentOS with cron scheduling, RBAC, OpenTelemetry tracing, and human-approval gates.
Description
Agno (formerly PhiData) is an Apache-2.0 Python SDK that frames the world as Agents — 'AI programs that use tools to accomplish tasks'. On top of agents it adds Teams with coordination modes (Coordinate / Route / Broadcast / Sequential), step-based Workflows, persistent Memory with a MemoryManager for LLM-driven user-memory extraction, Agentic-RAG via the Knowledge module, and 100+ integration Toolkits including MCPTools (stdio / SSE / streamable HTTP). The companion AgentOS platform exposes the runtime and a control plane for scheduled jobs, RBAC, OTel tracing, and human-approval gates.
Solution
Stateful tool-calling loop. Each Agent run assembles instructions, knowledge (RAG), memory, and tool schemas; the model emits tool calls or a final reply; tool results are appended and the loop iterates until the model returns text or hits a cap. Team wraps this loop with a leader+members topology selected via mode: Coordinate (leader picks members, crafts tasks, synthesises), Route (leader routes to one specialist), Broadcast (same task to all members), Sequential (chain agent responses). With persistent memory enabled the agent stores user memories across runs, sessions, and agents.
Primary use cases
- multi-agent teams with Coordinate / Route / Broadcast / Sequential modes
- Agentic RAG via the Knowledge module
- persistent user memory across runs and sessions
- production agent platform via AgentOS (cron + RBAC + OTel)
- MCP-integrated agents with 100+ toolkit integrations
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