agentops vs Tracely-ai
agentops is much bigger: 5.8k stars against 1.2k. Over the days we have tracked them agentops moved +3.8% and Tracely-ai +18.6%, so Tracely-ai is growing faster right now.
Tracely-ai leads on noise control and setup ease. agentops does not take any axis by a clear margin.
Stars and commit dates come from our own daily tracking. The six axes are read off each project's documentation by our review pipeline, so they describe what a project says about itself, not what we measured in its code.
Where they stand today
Provides end-to-end agent session replays, LLM cost tracking and debugging across many agent frameworks with minimal instrumentation.
- Stars
- 5.8k
- Tracked growth
- +3.8%
- Maturity
- ●●●●●
- Last commit
- 72d ago
- Language
- Python
- License
- MIT
- Cost to run
- AgentOps API key for hosted dashboard; can self-host
Promotes real failing production traces into hermetic, replayable regression cases that run offline in CI and block PRs, instead of relying on hand-authored datasets.
- Stars
- 1.2k
- Tracked growth
- +18.6%
- Maturity
- ●●●●●
- Last commit
- 5h ago
- Language
- Python
- License
- MIT
- Cost to run
- CI replay $0; live judges use your model API key.
Six axes, head to head
Each axis runs 0 to 5. The label under a score is what that project's own docs claim, not a category average.
| Axis | agentops | Tracely-ai |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Runtime tracing | ●●●●● Per-run only |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● None mentioned | ●●●●● Clustering & gating |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Config options | ●●●●● Rich rule & prompts |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Self-hostable | ●●●●● Self-hostable |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● Bring-your-own-key | ●●●●● Bring-your-key |
Setup ease What it takes to get a first useful run out of it. | ●●●●● API key + init | ●●●●● One-command demo |
Which one to pick
Pick agentops if…
Easy integration — one-line initialization (agentops.init) yields session replays, LLM call tracking, and cost analytics across multiple agent frameworks, with an option to self-host.
Pick Tracely-ai if…
Production-driven tests — pick Tracely when you want failing runs promoted from real traces into deterministic, offline regression cases that gate PRs.
- Noise control: Clustering & gating (4/5 against 1/5)
- Setup ease: One-command demo (5/5 against 3/5)
What people want from each one
AgentOps-AI/agentops
Questions people ask
Is agentops better than Tracely-ai?
Tracely-ai leads on noise control and setup ease. agentops does not take any axis by a clear margin. agentops is worth picking when easy integration — one-line initialization (agentops.init) yields session replays, LLM call tracking, and cost analytics across multiple agent frameworks, with an option to self-host.
Which of agentops and Tracely-ai keeps my code private?
agentops: Self-hostable (4/5). Tracely-ai: Self-hostable (4/5).
What does each one cost to run?
agentops: AgentOps API key for hosted dashboard; can self-host. Tracely-ai: CI replay $0; live judges use your model API key..
Full profiles: AgentOps-AI/agentops and Jwuthri/Tracely-ai. Everything else in Observability & tracing.