--- title: "agent-control vs agentops" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentcontrol-agent-control-vs-agentops-ai-agentops" tools: ["agentcontrol-agent-control", "agentops-ai-agentops"] --- # agent-control vs agentops *GraphCanon updated Sep 20, 2026* ## Verdict Pick agent-control if agent-control is a highly configurable and extensible centralized agent control system that governs runtime behavior of agents at scale via UI or SDK/API; pick agentops if agentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage. [agent-control](https://agentcontrol.dev) reports 305 GitHub stars, 51 forks, and 36 open issues, last pushed Sep 9, 2026. [agentops](https://agentops.ai) has 5.8k stars, 625 forks, and 184 open issues, last pushed Jun 25, 2026. Figures are from public GitHub metadata via [agent-control's repository](https://github.com/agentcontrol/agent-control) and [agentops's repository](https://github.com/AgentOps-AI/agentops). | | [agent-control](/tools/agentcontrol-agent-control.md) | [agentops](/tools/agentops-ai-agentops.md) | | --- | --- | --- | | Tagline | Centralized agent control plane for governing runtime agent behavior at scale | Python SDK for AI agent monitoring and LLM cost tracking | | Stars | 305 | 5,830 | | Forks | 51 | 625 | | Open issues | 36 | 184 | | Language | Python | Python | | Adopt for | agent-control is a highly configurable and extensible centralized agent control system that governs runtime behavior of agents at scale via UI or SDK/API. | AgentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | AI Agents | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agent-control](/tools/agentcontrol-agent-control.md) | [agentops](/tools/agentops-ai-agentops.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 1d | 86d | | Open issues (now) | 36 | 184 | | Stars delta | +16 (30d) | +59 (30d) | | Open issues delta | 0 (30d) | +8 (30d) | | Full report | [trust report](/tools/agentcontrol-agent-control/trust.md) | [trust report](/tools/agentops-ai-agentops/trust.md) | ## Shared compatibility - **Python**: [agent-control](/tools/agentcontrol-agent-control.md) - Python runtime; [agentops](/tools/agentops-ai-agentops.md) - Python runtime ## Decision facts: agent-control - **Adopt for:** agent-control is a highly configurable and extensible centralized agent control system that governs runtime behavior of agents at scale via UI or SDK/API. ## 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. ## Choose when ### Choose agent-control if… - License: agent-control is Apache-2.0, agentops is MIT. - Tags unique to agent-control: agentic-workflow, ai-safety, guardrails, llm. - agent-control ships Docker support for self-hosted deployment. - Use agent-control if you need to centrally manage the behavior of multiple AI agents in production environments. ### Choose agentops if… - License: agentops is MIT, agent-control is Apache-2.0. - Tags unique to agentops: ai-agents, benchmarking, cost-tracking. - Also covers Evaluation & Observability. - Integrations are needed specifically with Langchain, CrewAI, or OpenAI Agents SDK ## When NOT to use agent-control - Avoid using agent-control when your project does not require centralized control for large-scale AI agent management. - Not recommended if your setup is simplistic or relies solely on languages other than Python or TypeScript, since the tool primarily supports these two. ## 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 ## Common questions ### What is the difference between agent-control and agentops? agent-control: Centralized agent control plane for governing runtime agent behavior at scale. agentops: Python SDK for AI agent monitoring and LLM cost tracking. See the comparison table for live GitHub stats and shared categories. ### When should I choose agent-control over agentops? Choose agent-control over agentops when License: agent-control is Apache-2.0, agentops is MIT; Tags unique to agent-control: agentic-workflow, ai-safety, guardrails, llm; agent-control ships Docker support for self-hosted deployment; Use agent-control if you need to centrally manage the behavior of multiple AI agents in production environments. ### When should I choose agentops over agent-control? Choose agentops over agent-control when License: agentops is MIT, agent-control is Apache-2.0; Tags unique to agentops: ai-agents, benchmarking, cost-tracking; Also covers Evaluation & Observability; Integrations are needed specifically with Langchain, CrewAI, or OpenAI Agents SDK. ### When should I avoid agent-control? Avoid using agent-control when your project does not require centralized control for large-scale AI agent management. Not recommended if your setup is simplistic or relies solely on languages other than Python or TypeScript, since the tool primarily supports these two. ### 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 ### Is agent-control or agentops more popular on GitHub? agentops has more GitHub stars (5,830 vs 305). Stars measure visibility, not whether either tool fits your constraints. ### Are agent-control and agentops open source? Yes - both are open-source projects on GitHub (agent-control: Apache-2.0, agentops: MIT). ### Where can I find alternatives to agent-control or agentops? GraphCanon lists graph-backed alternatives at [agent-control alternatives](/tools/agentcontrol-agent-control/alternatives) and [agentops alternatives](/tools/agentops-ai-agentops/alternatives) ([agent-control markdown twin](/tools/agentcontrol-agent-control/alternatives.md), [agentops markdown twin](/tools/agentops-ai-agentops/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/agentcontrol-agent-control-vs-agentops-ai-agentops.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agent-control or agentops? agent-control: Very active. agentops: Steady. 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 agent-control and agentops? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agent-control trust report](/tools/agentcontrol-agent-control/trust); [agentops trust report](/tools/agentops-ai-agentops/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agentcontrol-agent-control`](/api/graphcanon/graph?tool=agentcontrol-agent-control) - 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/_