Comparison
agentops vs arthur-engine
Verdict
Pick agentops if agentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage; pick arthur-engine if the Arthur Engine monitors AI/ML workloads with a focus on guardrails for LLM applications, evaluation of agentic systems, extensive model monitoring metrics, and extensible API support.
Markdown twin · agentops alternatives · arthur-engine alternatives
GraphCanon updated Sep 20, 2026
9views this month
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Trust & integrity
| Signal | agentops | arthur-engine |
|---|---|---|
| Maintenance | Steady (86d since push) As of Sep 20, 2026 · github_public_v1 | Very active (0d since push) As of Sep 12, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 12, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- agentops
- Python SDK for AI agent monitoring and LLM cost tracking
- arthur-engine
- Monitoring and governing for your AI/ML
Stars
- agentops
- 5.8k
- arthur-engine
- 89
Forks
- agentops
- 625
- arthur-engine
- 16
Open issues
- agentops
- 184
- arthur-engine
- 16
Language
- agentops
- Python
- arthur-engine
- Python
Adopt for
- agentops
- AgentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage.
- arthur-engine
- The Arthur Engine monitors AI/ML workloads with a focus on guardrails for LLM applications, evaluation of agentic systems, extensive model monitoring metrics, and extensible API support.
Persona
- agentops
- -
- arthur-engine
- -
Runtime
- agentops
- -
- arthur-engine
- -
License
- agentops
- MIT
- arthur-engine
- MIT License, allowing free use and modification of the tool's codebase under the terms of this license.
Last pushed
- agentops
- Jun 25, 2026
- arthur-engine
- Sep 12, 2026
Categories
- agentops
- AI Agents, Evaluation & Observability
- arthur-engine
- Evaluation & Observability, Model Training
Trust and health
Maintenance
- agentops
- Steady (60%)
- arthur-engine
- Very active (96%)
Days since push
- agentops
- 86d
- arthur-engine
- 0d
Open issues (now)
- agentops
- 184
- arthur-engine
- 16
Stars delta
- agentops
- +59 (30d)
- arthur-engine
- +3 (30d)
Open issues delta
- agentops
- +8 (30d)
- arthur-engine
- -16 (30d)
Full report
- agentops
- Trust report
- arthur-engine
- Trust report
Choose agentops if…
- Tags unique to agentops: ai-agents, cost-tracking.
- Also covers AI Agents.
- Integrations are needed specifically with Langchain, CrewAI, or OpenAI Agents SDK
When NOT to use agentops
- If specific integration support is needed for frameworks not listed including Autogen AG2 CamelAI
- In case self-hosting of components is impractical due to resource constraints
Choose arthur-engine if…
- Tags unique to arthur-engine: agentic, evaluation, genai, guardrails.
- Also covers Model Training.
- When developing or managing large language models that require real-time detection of sensitive data leakage, hallucination, or prompt injection.
When NOT to use arthur-engine
- Avoid if the project does not require real-time monitoring and evaluation on live data streams.
- Not suitable for teams that prefer minimalistic setups over comprehensive services with wide-ranging capabilities.
- It may be overkill for organizations focused exclusively on model training without subsequent need for ongoing monitoring or governance.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (AgentOps-AI/agentops) · observed Sep 20, 2026
- GitHub forks (AgentOps-AI/agentops) · observed Sep 20, 2026
- Last push (AgentOps-AI/agentops) · observed Jun 25, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (arthur-ai/arthur-engine) · observed Sep 20, 2026
- GitHub forks (arthur-ai/arthur-engine) · observed Sep 20, 2026
- Last push (arthur-ai/arthur-engine) · observed Sep 12, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: agentops 5.8k · arthur-engine 89 (synced Sep 20, 2026).
Common questions
- What is the difference between agentops and arthur-engine?
- agentops: Python SDK for AI agent monitoring and LLM cost tracking. arthur-engine: Monitoring and governing for your AI/ML. See the comparison table for live GitHub stats and shared categories.
- When should I choose agentops over arthur-engine?
- Choose agentops over arthur-engine when Tags unique to agentops: ai-agents, cost-tracking; Also covers AI Agents; Integrations are needed specifically with Langchain, CrewAI, or OpenAI Agents SDK.
- When should I choose arthur-engine over agentops?
- Choose arthur-engine over agentops when Tags unique to arthur-engine: agentic, evaluation, genai, guardrails; Also covers Model Training; When developing or managing large language models that require real-time detection of sensitive data leakage, hallucination, or prompt injection.
- When should I avoid agentops?
- If specific integration support is needed for frameworks not listed including Autogen AG2 CamelAI In case self-hosting of components is impractical due to resource constraints
- When should I avoid arthur-engine?
- Avoid if the project does not require real-time monitoring and evaluation on live data streams. Not suitable for teams that prefer minimalistic setups over comprehensive services with wide-ranging capabilities. It may be overkill for organizations focused exclusively on model training without subsequent need for ongoing monitoring or governance.
- Is agentops or arthur-engine more popular on GitHub?
- agentops has more GitHub stars (5,830 vs 89). Stars measure visibility, not whether either tool fits your constraints.
- Are agentops and arthur-engine open source?
- Yes - both are open-source projects on GitHub (agentops: MIT, arthur-engine: MIT).
- Where can I find alternatives to agentops or arthur-engine?
- GraphCanon lists graph-backed alternatives at agentops alternatives and arthur-engine alternatives (agentops markdown twin, arthur-engine markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, agentops or arthur-engine?
- agentops: Steady. arthur-engine: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for agentops and arthur-engine?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentops trust report; arthur-engine trust report.