Agno

Health v2 · maintenance only

Adoption not part of the score

42675 stars · 6117 forks observed · 2026-10-12

What it is AI-extracted, prompt v1, taxonomy v1, 2026-09-28, confidence 0.97

Agno is a Python‑based SDK and runtime for building, deploying, and managing AI agent platforms. It provides a full stack—from agent definition to REST/MCP APIs, storage, scheduling, tracing, and a web UI control plane.

Use cases

• build a customer‑facing chatbot that can call external tools
• create internal AI assistants for document processing and data labeling
• run autonomous agents as a scalable microservice with REST and SSE endpoints
• manage multiple agents, teams, and workflows from a single web UI
• integrate LLMs with custom toolkits and store session memory in a database
• expose agents to other services via the MCP protocol

When to choose

• you need a unified framework to develop, serve, and govern AI agents
• you want built‑in JWT‑based RBAC and session management
• you require a REST/MCP API with streaming and background job support
• you plan to run agents on Docker, Kubernetes, or other cloud environments
• you want out‑of‑the‑box integrations with 100+ tools and vector storage

When to avoid

• you only need a lightweight single‑agent client library
• your project is not Python‑centric or requires a different language runtime
• you prefer a fully managed SaaS solution instead of self‑hosting
• you need a minimal CLI tool without a full control plane

Facets

framework · maturity active

api-framework http-server auth scheduling tracing llm-inference mcp cli large-language-models cloud-computing python cli cloud self-hosted agent-platform control-plane mcp-server jwt-rbac fastapi observability storage agent-sdk ai-agents retrieval-augmented-generation devops docker web-server

Member repositories

For agents

markdown · JSON · MCP: product_card(name="agno-agi/agno")