--- title: "agentops vs superagent" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentops-ai-agentops-vs-superagent-ai-superagent" tools: ["agentops-ai-agentops", "superagent-ai-superagent"] --- # agentops vs superagent *GraphCanon updated Aug 14, 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 superagent if superagent is an open-source SDK designed to protect AI applications from prompt injections, data leaks, and harmful outputs. It supports integration directly within TypeScript or Python applications. [agentops](https://agentops.ai) reports 5.8k GitHub stars, 612 forks, and 176 open issues, last pushed Jun 25, 2026. [superagent](https://superagent.sh) has 6.7k stars, 965 forks, and 12 open issues, last pushed Aug 13, 2026. Figures are from public GitHub metadata via [agentops's repository](https://github.com/AgentOps-AI/agentops) and [superagent's repository](https://github.com/superagent-ai/superagent). | | [agentops](/tools/agentops-ai-agentops.md) | [superagent](/tools/superagent-ai-superagent.md) | | --- | --- | --- | | Tagline | Python SDK for AI agent monitoring and LLM cost tracking | Superagent SDK | | Stars | 5,771 | 6,713 | | Forks | 612 | 965 | | Open issues | 176 | 12 | | Language | Python | TypeScript | | Adopt for | AgentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage. | Superagent is an open-source SDK designed to protect AI applications from prompt injections, data leaks, and harmful outputs. It supports integration directly within TypeScript or Python applications. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT License permits use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the SDK, provided that copyright notices and license texts accompany any distributed parts. | | Categories | AI Agents, Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentops](/tools/agentops-ai-agentops.md) | [superagent](/tools/superagent-ai-superagent.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 49d | 0d | | Open issues (now) | 176 | 12 | | Stars delta | Unknown | +41 (30d) | | Open issues delta | Unknown | 0 (30d) | | Full report | [trust report](/tools/agentops-ai-agentops/trust.md) | [trust report](/tools/superagent-ai-superagent/trust.md) | ## Shared compatibility - **Python**: [agentops](/tools/agentops-ai-agentops.md) - Python runtime; [superagent](/tools/superagent-ai-superagent.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: superagent - **Hosting:** managed - Superagent requires integrating their API via an SDK for TypeScript or Python applications. Users must obtain an API key for accessing these services. - **Adopt for:** Superagent is an open-source SDK designed to protect AI applications from prompt injections, data leaks, and harmful outputs. It supports integration directly within TypeScript or Python applications. - **License detail:** MIT License permits use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the SDK, provided that copyright notices and license texts accompany any distributed parts. ## Choose when ### Choose agentops if… - agentops is primarily Python; superagent is TypeScript. - Tags unique to agentops: ai-agents, benchmarking, cost-tracking. - Also covers AI Agents. - Integrations are needed specifically with Langchain, CrewAI, or OpenAI Agents SDK ### Choose superagent if… - superagent is primarily TypeScript; agentops is Python. - Superagent requires integrating their API via an SDK for TypeScript or Python applications. Users must obtain an API key for accessing these services. - Tags unique to superagent: ai, anthropic, guardrails, llm. - Use Superagent when you need a proactive solution that can detect and block malicious activities such as prompt injections and redact personal information automatically. ## 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 superagent - Avoid using Superagent when your project does not require the specific safety measures it offers, such as prompt injection prevention or scanning GitHub repositories for malicious activities. - If another tool in the same category provides better coverage or more advanced features that are critical to your application's security needs and aligns closer with your tech stack. ## Common questions ### What is the difference between agentops and superagent? agentops: Python SDK for AI agent monitoring and LLM cost tracking. superagent: Superagent SDK. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentops over superagent? Choose agentops over superagent when agentops is primarily Python; superagent is TypeScript; Tags unique to agentops: ai-agents, benchmarking, cost-tracking; Also covers AI Agents; Integrations are needed specifically with Langchain, CrewAI, or OpenAI Agents SDK. ### When should I choose superagent over agentops? Choose superagent over agentops when superagent is primarily TypeScript; agentops is Python; Superagent requires integrating their API via an SDK for TypeScript or Python applications. Users must obtain an API key for accessing these services; Tags unique to superagent: ai, anthropic, guardrails, llm; Use Superagent when you need a proactive solution that can detect and block malicious activities such as prompt injections and redact personal information automatically. ### 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 superagent? Avoid using Superagent when your project does not require the specific safety measures it offers, such as prompt injection prevention or scanning GitHub repositories for malicious activities. If another tool in the same category provides better coverage or more advanced features that are critical to your application's security needs and aligns closer with your tech stack. ### Is agentops or superagent more popular on GitHub? superagent has more GitHub stars (6,713 vs 5,771). Stars measure visibility, not whether either tool fits your constraints. ### Are agentops and superagent open source? Yes - both are open-source projects on GitHub (agentops: MIT, superagent: MIT). ### Where can I find alternatives to agentops or superagent? GraphCanon lists graph-backed alternatives at [agentops alternatives](/tools/agentops-ai-agentops/alternatives) and [superagent alternatives](/tools/superagent-ai-superagent/alternatives) ([agentops markdown twin](/tools/agentops-ai-agentops/alternatives.md), [superagent markdown twin](/tools/superagent-ai-superagent/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-superagent-ai-superagent.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentops or superagent? agentops: Steady. superagent: 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 superagent? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentops trust report](/tools/agentops-ai-agentops/trust); [superagent trust report](/tools/superagent-ai-superagent/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/_