--- title: "agentops vs RagaAI-Catalyst" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentops-ai-agentops-vs-raga-ai-hub-ragaai-catalyst" tools: ["agentops-ai-agentops", "raga-ai-hub-ragaai-catalyst"] --- # agentops vs RagaAI-Catalyst *GraphCanon updated Sep 20, 2026* ## 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 RagaAI-Catalyst if ragaAI-Catalyst emerges as a specialized Python framework designed for monitoring and evaluating AI agents, with unique features around self-hosted dashboards, advanced analytics, and support for tracing and debugging LL. [agentops](https://agentops.ai) reports 5.8k GitHub stars, 625 forks, and 184 open issues, last pushed Jun 25, 2026. [RagaAI-Catalyst](https://catalyst.raga.ai/) has 16k stars, 3.6k forks, and 34 open issues, last pushed Feb 11, 2026. Figures are from public GitHub metadata via [agentops's repository](https://github.com/AgentOps-AI/agentops) and [RagaAI-Catalyst's repository](https://github.com/raga-ai-hub/RagaAI-Catalyst). | | [agentops](/tools/agentops-ai-agentops.md) | [RagaAI-Catalyst](/tools/raga-ai-hub-ragaai-catalyst.md) | | --- | --- | --- | | Tagline | Python SDK for AI agent monitoring and LLM cost tracking | Python SDK for AI agent observability and evaluation | | Stars | 5,830 | 16,162 | | Forks | 625 | 3,567 | | Open issues | 184 | 34 | | Language | Python | Python | | Adopt for | AgentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage. | RagaAI-Catalyst emerges as a specialized Python framework designed for monitoring and evaluating AI agents, with unique features around self-hosted dashboards, advanced analytics, and support for tracing and debugging LL | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | AI Agents, Evaluation & Observability | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentops](/tools/agentops-ai-agentops.md) | [RagaAI-Catalyst](/tools/raga-ai-hub-ragaai-catalyst.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Slowing (36%) | | Days since push | 86d | 220d | | Open issues (now) | 184 | 34 | | Stars delta | +59 (30d) | +14 (30d) | | Open issues delta | +8 (30d) | 0 (30d) | | Full report | [trust report](/tools/agentops-ai-agentops/trust.md) | [trust report](/tools/raga-ai-hub-ragaai-catalyst/trust.md) | ## Shared compatibility - **Python**: [agentops](/tools/agentops-ai-agentops.md) - Python runtime; [RagaAI-Catalyst](/tools/raga-ai-hub-ragaai-catalyst.md) - Python runtime ## Decision facts: agentops - **Adopt for:** AgentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage. ## Decision facts: RagaAI-Catalyst - **Adopt for:** RagaAI-Catalyst emerges as a specialized Python framework designed for monitoring and evaluating AI agents, with unique features around self-hosted dashboards, advanced analytics, and support for tracing and debugging LL ## Choose when ### Choose agentops if… - License: agentops is MIT, RagaAI-Catalyst is Apache-2.0. - Tags unique to agentops: ai-agents, benchmarking, cost-tracking. - Integrations are needed specifically with Langchain, CrewAI, or OpenAI Agents SDK ### Choose RagaAI-Catalyst if… - License: RagaAI-Catalyst is Apache-2.0, agentops is MIT. - Tags unique to RagaAI-Catalyst: agentic-ai, agentic-ai-development, agentneo, agents. - When you need comprehensive tools for the observability of complex multi-agentic systems. ## 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 ## When NOT to use RagaAI-Catalyst - When you prefer a language-agnostic solution or require support outside of the Python ecosystem. - If your primary need is focused solely on basic monitoring without advanced debugging and evaluation features. - For projects that do not utilize multi-agentic systems or do not benefit from timeline and execution graph visualizations. - In scenarios where a fully managed service with no self-hosting requirements is preferred. ## Common questions ### What is the difference between agentops and RagaAI-Catalyst? agentops: Python SDK for AI agent monitoring and LLM cost tracking. RagaAI-Catalyst: Python SDK for AI agent observability and evaluation. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentops over RagaAI-Catalyst? Choose agentops over RagaAI-Catalyst when License: agentops is MIT, RagaAI-Catalyst is Apache-2.0; Tags unique to agentops: ai-agents, benchmarking, cost-tracking; Integrations are needed specifically with Langchain, CrewAI, or OpenAI Agents SDK. ### When should I choose RagaAI-Catalyst over agentops? Choose RagaAI-Catalyst over agentops when License: RagaAI-Catalyst is Apache-2.0, agentops is MIT; Tags unique to RagaAI-Catalyst: agentic-ai, agentic-ai-development, agentneo, agents; When you need comprehensive tools for the observability of complex multi-agentic systems. ### 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 RagaAI-Catalyst? When you prefer a language-agnostic solution or require support outside of the Python ecosystem. If your primary need is focused solely on basic monitoring without advanced debugging and evaluation features. For projects that do not utilize multi-agentic systems or do not benefit from timeline and execution graph visualizations. In scenarios where a fully managed service with no self-hosting requirements is preferred. ### Is agentops or RagaAI-Catalyst more popular on GitHub? RagaAI-Catalyst has more GitHub stars (16,162 vs 5,830). Stars measure visibility, not whether either tool fits your constraints. ### Are agentops and RagaAI-Catalyst open source? Yes - both are open-source projects on GitHub (agentops: MIT, RagaAI-Catalyst: Apache-2.0). ### Where can I find alternatives to agentops or RagaAI-Catalyst? GraphCanon lists graph-backed alternatives at [agentops alternatives](/tools/agentops-ai-agentops/alternatives) and [RagaAI-Catalyst alternatives](/tools/raga-ai-hub-ragaai-catalyst/alternatives) ([agentops markdown twin](/tools/agentops-ai-agentops/alternatives.md), [RagaAI-Catalyst markdown twin](/tools/raga-ai-hub-ragaai-catalyst/alternatives.md)), 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](/compare/agentops-ai-agentops-vs-raga-ai-hub-ragaai-catalyst.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentops or RagaAI-Catalyst? agentops: Steady. RagaAI-Catalyst: Slowing. 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 RagaAI-Catalyst? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentops trust report](/tools/agentops-ai-agentops/trust); [RagaAI-Catalyst trust report](/tools/raga-ai-hub-ragaai-catalyst/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agentops-ai-agentops`](/api/graphcanon/graph?tool=agentops-ai-agentops) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_