Comparison
agentops vs traceAI
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 traceAI if traceAI is an open-source observability framework for AI applications, built on OpenTelemetry, that provides structured tracing for LLM calls, prompts, token counts, retrieval steps, and agent decisions.
Markdown twin · agentops alternatives · traceAI alternatives
GraphCanon updated Sep 20, 2026
10views this month
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Trust & integrity
| Signal | agentops | traceAI |
|---|---|---|
| Maintenance | Steady (86d since push) As of Sep 20, 2026 · github_public_v1 | Active (21d since push) As of Sep 18, 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 18, 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 Sep 18, 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
- traceAI
- Open-source observability for AI applications
Stars
- agentops
- 5.8k
- traceAI
- 221
Forks
- agentops
- 625
- traceAI
- 44
Open issues
- agentops
- 184
- traceAI
- 15
Language
- agentops
- Python
- traceAI
- Python
Adopt for
- agentops
- AgentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage.
- traceAI
- traceAI is an open-source observability framework for AI applications, built on OpenTelemetry, that provides structured tracing for LLM calls, prompts, token counts, retrieval steps, and agent decisions.
Persona
- agentops
- -
- traceAI
- -
Runtime
- agentops
- -
- traceAI
- -
License
- agentops
- MIT
- traceAI
- traceAI is available under the Apache-2.0 license, allowing for free use, modification, and distribution.
Last pushed
- agentops
- Jun 25, 2026
- traceAI
- Aug 27, 2026
Categories
- agentops
- AI Agents, Evaluation & Observability
- traceAI
- Evaluation & Observability
Trust and health
Maintenance
- agentops
- Steady (60%)
- traceAI
- Active (82%)
Days since push
- agentops
- 86d
- traceAI
- 21d
Open issues (now)
- agentops
- 184
- traceAI
- 15
Stars delta
- agentops
- +59 (30d)
- traceAI
- +9 (30d)
Open issues delta
- agentops
- +8 (30d)
- traceAI
- +4 (30d)
Full report
- agentops
- Trust report
- traceAI
- Trust report
Shared compatibility
- Python · agentops: Python runtime · traceAI: Python runtime
Choose agentops if…
- License: agentops is MIT, traceAI is Apache-2.0.
- Tags unique to agentops: benchmarking, 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 traceAI if…
- License: traceAI is Apache-2.0, agentops is MIT.
- Pricing: traceAI is free and open-source, but users may incur costs based on the backend services they choose to integrate with..
- Requirements: Min 2 GB RAM; Python, TypeScript, Java, and C# are supported.; Requires OpenTelemetry-compatible backend for trace storage and visualization..
- Tags unique to traceAI: ai, langchain, large-language-models, observability.
- When you need to trace every LLM call, prompt, token count, retrieval step, and agent decision in your AI application.
When NOT to use traceAI
- If your project does not require detailed tracing of LLM calls, prompts, token counts, retrieval steps, and agent decisions.
- When you are working exclusively with a single AI framework that does not require cross-language consistency.
- If you are looking for a solution that is not open-source or does not support OpenTelemetry.
- When you prefer a vendor-specific solution over a vendor-agnostic approach.
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 (future-agi/traceAI) · observed Sep 20, 2026
- GitHub forks (future-agi/traceAI) · observed Sep 20, 2026
- Last push (future-agi/traceAI) · observed Aug 27, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: agentops 5.8k · traceAI 221 (synced Sep 20, 2026).
Common questions
- What is the difference between agentops and traceAI?
- agentops: Python SDK for AI agent monitoring and LLM cost tracking. traceAI: Open-source observability for AI applications. See the comparison table for live GitHub stats and shared categories.
- When should I choose agentops over traceAI?
- Choose agentops over traceAI when License: agentops is MIT, traceAI is Apache-2.0; Tags unique to agentops: benchmarking, cost-tracking; Also covers AI Agents; Integrations are needed specifically with Langchain, CrewAI, or OpenAI Agents SDK.
- When should I choose traceAI over agentops?
- Choose traceAI over agentops when License: traceAI is Apache-2.0, agentops is MIT; Pricing: traceAI is free and open-source, but users may incur costs based on the backend services they choose to integrate with.; Requirements: Min 2 GB RAM; Python, TypeScript, Java, and C# are supported.; Requires OpenTelemetry-compatible backend for trace storage and visualization.; Tags unique to traceAI: ai, langchain, large-language-models, observability; When you need to trace every LLM call, prompt, token count, retrieval step, and agent decision in your AI application.
- 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 traceAI?
- If your project does not require detailed tracing of LLM calls, prompts, token counts, retrieval steps, and agent decisions. When you are working exclusively with a single AI framework that does not require cross-language consistency. If you are looking for a solution that is not open-source or does not support OpenTelemetry. When you prefer a vendor-specific solution over a vendor-agnostic approach.
- Is agentops or traceAI more popular on GitHub?
- agentops has more GitHub stars (5,830 vs 221). Stars measure visibility, not whether either tool fits your constraints.
- Are agentops and traceAI open source?
- Yes - both are open-source projects on GitHub (agentops: MIT, traceAI: Apache-2.0).
- Where can I find alternatives to agentops or traceAI?
- GraphCanon lists graph-backed alternatives at agentops alternatives and traceAI alternatives (agentops markdown twin, traceAI 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 traceAI?
- agentops: Steady. traceAI: 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 traceAI?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentops trust report; traceAI trust report.