OmO vs Agno
Side-by-side comparison of two AI agent tools
Short answer
- OmO is growing faster: +1,005 GitHub stars in the last 30 days vs +558 for Agno.
- Pick OmO for: omO: Just type "mass ulw" keyword with your prompt. Pick Agno for: build, run, manage agentic software at scale.
From GitHub data refreshed daily.
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OmOopen-source
OmO: Just type "mass ulw" keyword with your prompt. Now you are the master of graph engineering.
Agnoopen-source
Build, run, manage agentic software at scale.
Metrics
| OmO | Agno | |
|---|---|---|
| Stars | 69.8k | 42.5k |
| Star velocity /mo | 1.0k | 558.2539682539682 |
| Commits (90d) | 9.4k | 349 |
| Releases (6m) | 10 | 10 |
| Overall score | 0.9105351293499632 | 0.814447863455959 |
Pros
- +Production-ready runtime with built-in scalability, session isolation, and native tracing capabilities
- +Comprehensive monitoring and management through AgentOS UI for testing, debugging, and production oversight
- +Simple development experience - build sophisticated agents with memory and tools in approximately 20 lines of Python code
Cons
- -Python-focused platform with limited examples for other programming languages
- -Requires multiple dependencies and proper configuration of API keys and database connections
- -May have a learning curve for implementing complex multi-agent workflows and team coordination
Use Cases
- •Building production AI agents with persistent state, memory, and custom tool integrations for customer service or automation
- •Creating multi-agent teams and workflows for complex business processes that require coordination between specialized agents
- •Enterprise deployment of AI agents with comprehensive monitoring, user session management, and production-grade reliability requirements
FAQ
- Which is more popular, OmO or Agno?
- OmO has more GitHub stars (69,754 vs 42,494).
- Which is more actively developed, OmO or Agno?
- OmO had more commits in the last 90 days (9,367 vs 349).
- Should I use OmO or Agno?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.