crewai vs agno
Two of the top projects in Agent frameworks and SDKs, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
crewai
Python framework for multi-agent workflows with role-based Crews and event-driven Flows
agno
Python SDK and runtime for building and serving agents behind a REST API
Verdict
crewai ranks higher, 77 to 69. Of the 4 score parts we measure for both, crewai leads on 2, agno on 1 and 1 is even.
- Adoptioncrewai leads by 32 points, 63 to 31: a wide gap.
- FreshnessEven at 100.
- Maintenancecrewai leads by 6 points, 83 to 77.
- Agent-readyagno leads by 40 points, 70 to 30: a wide gap.
Pick crewai if you are
Python developers building multi-agent LLM workflows in code
- Two models: autonomous Crews and explicit Flows with state, branching and or_/and_ triggers
- CLI scaffolds projects; agents and tasks declared in JSONC or classic YAML
Pick agno if you are
Python developers building self-hosted multi-user agent services
- Runtime ships a REST API with 50+ endpoints, SSE and websockets
- JWT-based RBAC and multi-tenant isolation included
| What we compare | crewai | agno |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 63, popular | 31, known |
| Freshness | 100, active | 100, active |
| Maintenance | 83, healthy | 77, fair |
| Easy to run | Not scored for this kind | Not scored for this kind |
| Agent-ready | 30, minimal | 70, partly |
| Facts from GitHub and the README | ||
| Stars | 59.7k | 42.7k |
| License | MIT (permissive) | Apache-2.0 (permissive) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Oct 2026 | Oct 2026 |
| Language | Python | Python |
| Docker | No | No |
| GPU | Not needed | Not stated |
| arm64 or Apple Silicon | Not stated | Not stated |
crewai
CrewAI is a Python framework for building multi-agent workflows. Crews are teams of role-based agents with goals, tools and tasks, run sequentially or under a hierarchical manager. Flows are event-driven workflows with typed state, branching and routing that can embed Crews. A CLI scaffolds JSON-defined crew projects, with a classic YAML scaffold still available.
Who it is for: Python developers building multi-agent LLM workflows in code
Strengths
- Two models: autonomous Crews and explicit Flows with state, branching and or_/and_ triggers
- CLI scaffolds projects; agents and tasks declared in JSONC or classic YAML
- Covers tools, memory, knowledge, checkpointing, async execution and MCP/A2A support
- MIT license; recent commit and release within days of listing
Weaknesses
- Managed deployment, governance and enterprise support are in the commercial AMP Suite
- README has a telemetry section; opt-out details are not in the excerpt
- Requires Python >=3.10 and <3.14 and uv; Windows may need C++ build tools
- Web search example needs a separate Serper.dev API key
- no GPU
- Needs Python >=3.10,<3.14, uv, LLM provider API key, Serper.dev API key (optional, web search)
- Models: OpenAI (e.g. openai/gpt-4o), other providers via LLM setup
agno
Agno is a Python framework for defining agents, plus the AgentOS runtime that serves them through a REST API with 50+ endpoints, SSE and websockets. Sessions, memory, knowledge and traces are stored in your own database, and a web UI manages the running platform. It includes JWT-based RBAC, human approval steps, cron scheduling, and interfaces for Slack, Telegram, WhatsApp, Discord, AG-UI and A2A.
Who it is for: Python developers building self-hosted multi-user agent services
Strengths
- Runtime ships a REST API with 50+ endpoints, SSE and websockets
- JWT-based RBAC and multi-tenant isolation included
- 100+ prebuilt toolkits plus OpenTelemetry tracing and audit logs
- Starter templates for Docker, AWS, GCP, Azure, Fly, Render, Modal and Helm
Weaknesses
- Sends a telemetry event per agent run unless AGNO_TELEMETRY=false is set
- README gives no RAM, GPU or port requirements
- Starter templates live in separate repos, not in this one
- Management UI hosting and licensing terms are not described in the README
- Needs Postgres, Docker
- Models: unknown
More in Agent frameworks and SDKs
Building with these?
We help teams pick an open-source AI stack and run it in production. Client work never changes a rank.