--- title: "AgentGuard vs plano" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dipampaul17-agentguard-vs-katanemo-plano" tools: ["dipampaul17-agentguard", "katanemo-plano"] --- # AgentGuard vs plano *GraphCanon updated Aug 20, 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 plano if plano is an AI-native proxy and data plane for agentic applications built with Rust under the Apache-2.0 license, focusing on smart LLM routing capabilities alongside orchestration and observability features. [AgentGuard](https://github.com/dipampaul17/AgentGuard) reports 171 GitHub stars, 10 forks, and 1 open issues, last pushed Jul 31, 2025. [plano](https://planoai.dev) has 7.0k stars, 482 forks, and 138 open issues, last pushed Aug 19, 2026. Figures are from public GitHub metadata via [AgentGuard's repository](https://github.com/dipampaul17/AgentGuard) and [plano's repository](https://github.com/katanemo/plano). | | [AgentGuard](/tools/dipampaul17-agentguard.md) | [plano](/tools/katanemo-plano.md) | | --- | --- | --- | | Tagline | Real-time guardrail that monitors token spend and manages LLM/agent loops in real time | An AI-native proxy and data plane for agentic apps | | Stars | 171 | 7,004 | | Forks | 10 | 482 | | Open issues | 1 | 138 | | Language | JavaScript | Rust | | 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. | Plano is an AI-native proxy and data plane for agentic applications built with Rust under the Apache-2.0 license, focusing on smart LLM routing capabilities alongside orchestration and observability features. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Evaluation & Observability, Inference & Serving | AI Agents, Evaluation & Observability, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [AgentGuard](/tools/dipampaul17-agentguard.md) | [plano](/tools/katanemo-plano.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 373d | 0d | | Open issues (now) | 1 | 138 | | Stars delta | Unknown | +127 (30d) | | Open issues delta | Unknown | +7 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/dipampaul17-agentguard/trust.md) | [trust report](/tools/katanemo-plano/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: plano - **Pricing:** freemium - Freely available under Apache-2.0 license but potential for premium services around support and advanced features. - **Requirements:** Min 1 GB RAM - **Adopt for:** Plano is an AI-native proxy and data plane for agentic applications built with Rust under the Apache-2.0 license, focusing on smart LLM routing capabilities alongside orchestration and observability features. ## Choose when ### Choose AgentGuard if… - AgentGuard is primarily JavaScript; plano is Rust. - License: AgentGuard is MIT, plano is Apache-2.0. - Tags unique to AgentGuard: ai-agents, anthropic, cost-monitoring. - When you need precise control over spend and want live updates on token prices ### Choose plano if… - plano is primarily Rust; AgentGuard is JavaScript. - License: plano is Apache-2.0, AgentGuard is MIT. - Pricing: Freely available under Apache-2.0 license but potential for premium services around support and advanced features.. - Requirements: Min 1 GB RAM. - Tags unique to plano: agency-apps, ai-gateway, llm-proxy, llm-routing. - Also covers AI Agents. - plano ships Docker support for self-hosted deployment. - You are working on building complex multi-agent workflows where intelligent LLM (Language Model) routing is required. ## 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 plano - If your application does not require deep orchestration or smart routing between multiple models, choosing Plano might introduce unnecessary complexity. - For scenarios where minimal intervention routing is preferred without advanced observability and guardrail features, this tool may over-deliver on certain functionalities, possibly increasing overhead ## Common questions ### What is the difference between AgentGuard and plano? AgentGuard: Real-time guardrail that monitors token spend and manages LLM/agent loops in real time. plano: An AI-native proxy and data plane for agentic apps. See the comparison table for live GitHub stats and shared categories. ### When should I choose AgentGuard over plano? Choose AgentGuard over plano when AgentGuard is primarily JavaScript; plano is Rust; License: AgentGuard is MIT, plano is Apache-2.0; Tags unique to AgentGuard: ai-agents, anthropic, cost-monitoring; When you need precise control over spend and want live updates on token prices. ### When should I choose plano over AgentGuard? Choose plano over AgentGuard when plano is primarily Rust; AgentGuard is JavaScript; License: plano is Apache-2.0, AgentGuard is MIT; Pricing: Freely available under Apache-2.0 license but potential for premium services around support and advanced features.; Requirements: Min 1 GB RAM; Tags unique to plano: agency-apps, ai-gateway, llm-proxy, llm-routing; Also covers AI Agents; plano ships Docker support for self-hosted deployment; You are working on building complex multi-agent workflows where intelligent LLM (Language Model) routing is required. ### 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 plano? If your application does not require deep orchestration or smart routing between multiple models, choosing Plano might introduce unnecessary complexity. For scenarios where minimal intervention routing is preferred without advanced observability and guardrail features, this tool may over-deliver on certain functionalities, possibly increasing overhead ### Is AgentGuard or plano more popular on GitHub? plano has more GitHub stars (7,004 vs 171). Stars measure visibility, not whether either tool fits your constraints. ### Are AgentGuard and plano open source? Yes - both are open-source projects on GitHub (AgentGuard: MIT, plano: Apache-2.0). ### Where can I find alternatives to AgentGuard or plano? GraphCanon lists graph-backed alternatives at [AgentGuard alternatives](/tools/dipampaul17-agentguard/alternatives) and [plano alternatives](/tools/katanemo-plano/alternatives) ([AgentGuard markdown twin](/tools/dipampaul17-agentguard/alternatives.md), [plano markdown twin](/tools/katanemo-plano/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-katanemo-plano.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, AgentGuard or plano? AgentGuard: Dormant. plano: 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 AgentGuard and plano? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [AgentGuard trust report](/tools/dipampaul17-agentguard/trust); [plano trust report](/tools/katanemo-plano/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/_