--- title: "agent-control vs core" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentcontrol-agent-control-vs-cheshire-cat-ai-core" tools: ["agentcontrol-agent-control", "cheshire-cat-ai-core"] --- # agent-control vs core *GraphCanon updated Aug 15, 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 core if core is a Python-based AI microservice tool for building chatbots and integrating vector search. It supports conversational interfaces through the ag-ui-protocol. [agent-control](https://agentcontrol.dev) reports 289 GitHub stars, 44 forks, and 36 open issues, last pushed Aug 6, 2026. [core](https://cheshirecat.ai) has 3.1k stars, 409 forks, and 8 open issues, last pushed Jul 29, 2026. Figures are from public GitHub metadata via [agent-control's repository](https://github.com/agentcontrol/agent-control) and [core's repository](https://github.com/cheshire-cat-ai/core). | | [agent-control](/tools/agentcontrol-agent-control.md) | [core](/tools/cheshire-cat-ai-core.md) | | --- | --- | --- | | Tagline | Centralized agent control plane for governing runtime agent behavior at scale | AI agent microservice | | Stars | 289 | 3,081 | | Forks | 44 | 409 | | Open issues | 36 | 8 | | 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. | core is a Python-based AI microservice tool for building chatbots and integrating vector search. It supports conversational interfaces through the ag-ui-protocol. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | GPL-3.0 licenses the code base of the core repository. | | Categories | AI Agents | AI Agents, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agent-control](/tools/agentcontrol-agent-control.md) | [core](/tools/cheshire-cat-ai-core.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 2d | 16d | | Open issues (now) | 36 | 8 | | Stars delta | Unknown | +7 (30d) | | Open issues delta | Unknown | +1 (30d) | | Full report | [trust report](/tools/agentcontrol-agent-control/trust.md) | [trust report](/tools/cheshire-cat-ai-core/trust.md) | ## 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: core - **Hosting:** self hosted - core can be self-hosted. - **Requirements:** Requires Python support due to being Python-based. - **Adopt for:** core is a Python-based AI microservice tool for building chatbots and integrating vector search. It supports conversational interfaces through the ag-ui-protocol. - **License detail:** GPL-3.0 licenses the code base of the core repository. ## Choose when ### Choose agent-control if… - License: agent-control is Apache-2.0, core is GPL-3.0. - 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 core if… - License: core is GPL-3.0, agent-control is Apache-2.0. - core can be self-hosted. - Requirements: Requires Python support due to being Python-based.. - Tags unique to core: ag-ui-protocol, agent, ai, assistant. - Also covers Vector Databases. - For projects that require an open-source solution under GPL-3.0, because core's licensing aligns with this requirement ## 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 core - If your project needs proprietary license terms, since core restricts use by GPL-3.0 which might not fit all commercial scenarios - In cases where you require a non-Python environment, as the tool may require significant custom code to adapt to another language ## Common questions ### What is the difference between agent-control and core? agent-control: Centralized agent control plane for governing runtime agent behavior at scale. core: AI agent microservice. See the comparison table for live GitHub stats and shared categories. ### When should I choose agent-control over core? Choose agent-control over core when License: agent-control is Apache-2.0, core is GPL-3.0; 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 core over agent-control? Choose core over agent-control when License: core is GPL-3.0, agent-control is Apache-2.0; core can be self-hosted; Requirements: Requires Python support due to being Python-based.; Tags unique to core: ag-ui-protocol, agent, ai, assistant; Also covers Vector Databases; For projects that require an open-source solution under GPL-3.0, because core's licensing aligns with this requirement. ### 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 core? If your project needs proprietary license terms, since core restricts use by GPL-3.0 which might not fit all commercial scenarios In cases where you require a non-Python environment, as the tool may require significant custom code to adapt to another language ### Is agent-control or core more popular on GitHub? core has more GitHub stars (3,081 vs 289). Stars measure visibility, not whether either tool fits your constraints. ### Are agent-control and core open source? Yes - both are open-source projects on GitHub (agent-control: Apache-2.0, core: GPL-3.0). ### Where can I find alternatives to agent-control or core? GraphCanon lists graph-backed alternatives at [agent-control alternatives](/tools/agentcontrol-agent-control/alternatives) and [core alternatives](/tools/cheshire-cat-ai-core/alternatives) ([agent-control markdown twin](/tools/agentcontrol-agent-control/alternatives.md), [core markdown twin](/tools/cheshire-cat-ai-core/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-cheshire-cat-ai-core.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agent-control or core? agent-control: Very active. core: 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 agent-control and core? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agent-control trust report](/tools/agentcontrol-agent-control/trust); [core trust report](/tools/cheshire-cat-ai-core/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/_