--- title: "AgentGuard vs raga-llm-hub" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dipampaul17-agentguard-vs-raga-ai-hub-raga-llm-hub" tools: ["dipampaul17-agentguard", "raga-ai-hub-raga-llm-hub"] --- # AgentGuard vs raga-llm-hub *GraphCanon updated Aug 9, 2026* ## Verdict Pick AgentGuard if agentGuard is a budget-conscious observer for real-time token spending by AI agents and LLMs, integrating with major providers like OpenAI and Anthropic; pick raga-llm-hub if raga LLM-Hub is a Python-based framework for evaluating large language models, enforcing guardrails, and ensuring security during the operation of these models. [AgentGuard](https://github.com/dipampaul17/AgentGuard) reports 171 GitHub stars, 10 forks, and 1 open issues, last pushed Jul 31, 2025. [raga-llm-hub](https://www.raga.ai/llms) has 114 stars, 14 forks, and 2 open issues, last pushed Sep 9, 2024. Figures are from public GitHub metadata via [AgentGuard's repository](https://github.com/dipampaul17/AgentGuard) and [raga-llm-hub's repository](https://github.com/raga-ai-hub/raga-llm-hub). | | [AgentGuard](/tools/dipampaul17-agentguard.md) | [raga-llm-hub](/tools/raga-ai-hub-raga-llm-hub.md) | | --- | --- | --- | | Tagline | Real-time guardrail that monitors token spend and manages LLM/agent loops in real time | Framework for LLM evaluation, guardrails and security | | Stars | 171 | 114 | | Forks | 10 | 14 | | Open issues | 1 | 2 | | Language | JavaScript | Python | | Adopt for | AgentGuard is a budget-conscious observer for real-time token spending by AI agents and LLMs, integrating with major providers like OpenAI and Anthropic. | Raga LLM-Hub is a Python-based framework for evaluating large language models, enforcing guardrails, and ensuring security during the operation of these models. | | Persona | - | - | | Runtime | - | - | | License | MIT | The license for Raga LLM-Hub differs from common Open Source licenses like MIT or Apache, implying specific conditions that might affect its usability in open projects. | | Categories | Evaluation & Observability, Inference & Serving | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [AgentGuard](/tools/dipampaul17-agentguard.md) | [raga-llm-hub](/tools/raga-ai-hub-raga-llm-hub.md) | | --- | --- | --- | | Days since push | 373d | 687d | | Open issues (now) | 1 | 2 | | Owner type | User | Organization | | Full report | [trust report](/tools/dipampaul17-agentguard/trust.md) | [trust report](/tools/raga-ai-hub-raga-llm-hub/trust.md) | ## Decision facts: AgentGuard - **Adopt for:** AgentGuard is a budget-conscious observer for real-time token spending by AI agents and LLMs, integrating with major providers like OpenAI and Anthropic. ## Decision facts: raga-llm-hub - **Pricing:** unknown - Pricing information is not specified; it operates under a unique licensing model which may or may not have restrictive terms for commercial use. - **Requirements:** Requires Python installation and environment to set up.; Installation is straightforward through pip but the broader dependencies should be checked as per project requirements. - **Adopt for:** Raga LLM-Hub is a Python-based framework for evaluating large language models, enforcing guardrails, and ensuring security during the operation of these models. - **License detail:** The license for Raga LLM-Hub differs from common Open Source licenses like MIT or Apache, implying specific conditions that might affect its usability in open projects. ## Choose when ### Choose AgentGuard if… - AgentGuard is primarily JavaScript; raga-llm-hub is Python. - License: AgentGuard is MIT, raga-llm-hub is Other. - Tags unique to AgentGuard: ai-agents, anthropic, cost-monitoring, observability. - Also covers Inference & Serving. - When you need precise control over spend and want live updates on token prices ### Choose raga-llm-hub if… - raga-llm-hub is primarily Python; AgentGuard is JavaScript. - License: raga-llm-hub is Other, AgentGuard is MIT. - Pricing: Pricing information is not specified; it operates under a unique licensing model which may or may not have restrictive terms for commercial use.. - Requirements: Requires Python installation and environment to set up.; Installation is straightforward through pip but the broader dependencies should be checked as per project requirements.. - Tags unique to raga-llm-hub: guardrails, llm security, llm-evaluation, llmops. - When you need to conduct detailed evaluations on large language models and require specific methods to enforce guardrails and maintain security within your application or environment. ## When NOT to use AgentGuard - If you prioritize a different language for your project and cannot use JavaScript - In cases requiring more elaborate fallback mechanisms than what AgentGuard offers ## When NOT to use raga-llm-hub - If you are working in an environment where the use of Python is not feasible or desired, as Raga LLM-Hub's functionality is deeply integrated within Python. - Avoid using if your primary need does not include guardrails enforcement and security features for LLMs, since Raga LLM Hub emphasizes these aspects. ## Common questions ### What is the difference between AgentGuard and raga-llm-hub? AgentGuard: Real-time guardrail that monitors token spend and manages LLM/agent loops in real time. raga-llm-hub: Framework for LLM evaluation, guardrails and security. See the comparison table for live GitHub stats and shared categories. ### When should I choose AgentGuard over raga-llm-hub? Choose AgentGuard over raga-llm-hub when AgentGuard is primarily JavaScript; raga-llm-hub is Python; License: AgentGuard is MIT, raga-llm-hub is Other; Tags unique to AgentGuard: ai-agents, anthropic, cost-monitoring, observability; Also covers Inference & Serving; When you need precise control over spend and want live updates on token prices. ### When should I choose raga-llm-hub over AgentGuard? Choose raga-llm-hub over AgentGuard when raga-llm-hub is primarily Python; AgentGuard is JavaScript; License: raga-llm-hub is Other, AgentGuard is MIT; Pricing: Pricing information is not specified; it operates under a unique licensing model which may or may not have restrictive terms for commercial use.; Requirements: Requires Python installation and environment to set up.; Installation is straightforward through pip but the broader dependencies should be checked as per project requirements.; Tags unique to raga-llm-hub: guardrails, llm security, llm-evaluation, llmops; When you need to conduct detailed evaluations on large language models and require specific methods to enforce guardrails and maintain security within your application or environment. ### When should I avoid AgentGuard? If you prioritize a different language for your project and cannot use JavaScript In cases requiring more elaborate fallback mechanisms than what AgentGuard offers ### When should I avoid raga-llm-hub? If you are working in an environment where the use of Python is not feasible or desired, as Raga LLM-Hub's functionality is deeply integrated within Python. Avoid using if your primary need does not include guardrails enforcement and security features for LLMs, since Raga LLM Hub emphasizes these aspects. ### Is AgentGuard or raga-llm-hub more popular on GitHub? AgentGuard has more GitHub stars (171 vs 114). Stars measure visibility, not whether either tool fits your constraints. ### Are AgentGuard and raga-llm-hub open source? Yes - both are open-source projects on GitHub (AgentGuard: MIT, raga-llm-hub: Other). ### Where can I find alternatives to AgentGuard or raga-llm-hub? GraphCanon lists graph-backed alternatives at [AgentGuard alternatives](/tools/dipampaul17-agentguard/alternatives) and [raga-llm-hub alternatives](/tools/raga-ai-hub-raga-llm-hub/alternatives) ([AgentGuard markdown twin](/tools/dipampaul17-agentguard/alternatives.md), [raga-llm-hub markdown twin](/tools/raga-ai-hub-raga-llm-hub/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/dipampaul17-agentguard-vs-raga-ai-hub-raga-llm-hub.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, AgentGuard or raga-llm-hub? AgentGuard: Dormant. raga-llm-hub: Dormant. 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 AgentGuard and raga-llm-hub? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [AgentGuard trust report](/tools/dipampaul17-agentguard/trust); [raga-llm-hub trust report](/tools/raga-ai-hub-raga-llm-hub/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=dipampaul17-agentguard`](/api/graphcanon/graph?tool=dipampaul17-agentguard) - 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/_