--- title: "agentset vs llm-wiki-agent" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentset-ai-agentset-vs-samuraigpt-llm-wiki-agent" tools: ["agentset-ai-agentset", "samuraigpt-llm-wiki-agent"] --- # agentset vs llm-wiki-agent *GraphCanon updated Aug 22, 2026* ## Verdict Pick agentset if agentSet is a Retrieval-Augmented Generation (RAG) platform emphasizing built-in citations and support for deep research. It's designed to handle diverse file formats while ensuring effective memory management; pick llm-wiki-agent if llm-wiki-agent serves as a self-maintained personal knowledge base using AI agents like Claude, Codex, OpenCode, and Gemini CLI. [agentset](https://agentset.ai) reports 2.1k GitHub stars, 185 forks, and 14 open issues, last pushed Jul 16, 2026. [llm-wiki-agent](https://github.com/SamurAIGPT/llm-wiki-agent) has 3.3k stars, 388 forks, and 3 open issues, last pushed Aug 3, 2026. Figures are from public GitHub metadata via [agentset's repository](https://github.com/agentset-ai/agentset) and [llm-wiki-agent's repository](https://github.com/SamurAIGPT/llm-wiki-agent). | | [agentset](/tools/agentset-ai-agentset.md) | [llm-wiki-agent](/tools/samuraigpt-llm-wiki-agent.md) | | --- | --- | --- | | Tagline | The open-source RAG platform with built-in citations and support for deep research | A personal knowledge base that builds and maintains itself using various AI agents. | | Stars | 2,066 | 3,334 | | Forks | 185 | 388 | | Open issues | 14 | 3 | | Language | TypeScript | Python | | Adopt for | AgentSet is a Retrieval-Augmented Generation (RAG) platform emphasizing built-in citations and support for deep research. It's designed to handle diverse file formats while ensuring effective memory management. | llm-wiki-agent serves as a self-maintained personal knowledge base using AI agents like Claude, Codex, OpenCode, and Gemini CLI. | | Persona | - | - | | Runtime | - | - | | License | AgentSet operates under the MIT License, allowing for broad usage and modification rights. | MIT | | Categories | AI Agents, Data & Retrieval | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentset](/tools/agentset-ai-agentset.md) | [llm-wiki-agent](/tools/samuraigpt-llm-wiki-agent.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 36d | 5d | | Open issues (now) | 14 | 3 | | Stars delta | +31 (30d) | Unknown | | Open issues delta | +1 (30d) | Unknown | | Full report | [trust report](/tools/agentset-ai-agentset/trust.md) | [trust report](/tools/samuraigpt-llm-wiki-agent/trust.md) | ## Decision facts: agentset - **Pricing:** freemium - Free to use as it is open-source. - **Requirements:** Primarily developed in TypeScript.; Best used with an understanding of Retrieval-Augmented Generation and AI agent functionalities. - **Adopt for:** AgentSet is a Retrieval-Augmented Generation (RAG) platform emphasizing built-in citations and support for deep research. It's designed to handle diverse file formats while ensuring effective memory management. - **License detail:** AgentSet operates under the MIT License, allowing for broad usage and modification rights. ## Decision facts: llm-wiki-agent - **Adopt for:** llm-wiki-agent serves as a self-maintained personal knowledge base using AI agents like Claude, Codex, OpenCode, and Gemini CLI. ## Choose when ### Choose agentset if… - agentset is primarily TypeScript; llm-wiki-agent is Python. - Pricing: Free to use as it is open-source.. - Requirements: Primarily developed in TypeScript.; Best used with an understanding of Retrieval-Augmented Generation and AI agent functionalities.. - Tags unique to agentset: agentic-rag, ai-agents, embeddings, memory-management. - - Use AgentSet when you require deep integration with multiple file types including over 22 supported formats. ### Choose llm-wiki-agent if… - llm-wiki-agent is primarily Python; agentset is TypeScript. - Tags unique to llm-wiki-agent: ai-agent, automation, knowledge-base, llm. - When you need to create an interlinked wiki without setting up API keys or configuring Python environments. ## When NOT to use agentset - - Avoid selecting AgentSet if your application does not benefit from or necessitate support for a wide array of file types, as its complexity might overwhelm simpler use-cases. - - If seamless integration with third-party citation services is more preferred, another tool might be better suited since AgentSet focuses on built-in citation capabilities. ## When NOT to use llm-wiki-agent - If the process requires strict privacy controls and no third-party AI agents can be used. - When your project needs real-time interaction with APIs for dynamic content integration, as llm-wiki-agent does not support API-driven operations. ## Common questions ### What is the difference between agentset and llm-wiki-agent? agentset: The open-source RAG platform with built-in citations and support for deep research. llm-wiki-agent: A personal knowledge base that builds and maintains itself using various AI agents.. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentset over llm-wiki-agent? Choose agentset over llm-wiki-agent when agentset is primarily TypeScript; llm-wiki-agent is Python; Pricing: Free to use as it is open-source.; Requirements: Primarily developed in TypeScript.; Best used with an understanding of Retrieval-Augmented Generation and AI agent functionalities.; Tags unique to agentset: agentic-rag, ai-agents, embeddings, memory-management; - Use AgentSet when you require deep integration with multiple file types including over 22 supported formats. ### When should I choose llm-wiki-agent over agentset? Choose llm-wiki-agent over agentset when llm-wiki-agent is primarily Python; agentset is TypeScript; Tags unique to llm-wiki-agent: ai-agent, automation, knowledge-base, llm; When you need to create an interlinked wiki without setting up API keys or configuring Python environments. ### When should I avoid agentset? - Avoid selecting AgentSet if your application does not benefit from or necessitate support for a wide array of file types, as its complexity might overwhelm simpler use-cases. - If seamless integration with third-party citation services is more preferred, another tool might be better suited since AgentSet focuses on built-in citation capabilities. ### When should I avoid llm-wiki-agent? If the process requires strict privacy controls and no third-party AI agents can be used. When your project needs real-time interaction with APIs for dynamic content integration, as llm-wiki-agent does not support API-driven operations. ### Is agentset or llm-wiki-agent more popular on GitHub? llm-wiki-agent has more GitHub stars (3,334 vs 2,066). Stars measure visibility, not whether either tool fits your constraints. ### Are agentset and llm-wiki-agent open source? Yes - both are open-source projects on GitHub (agentset: MIT, llm-wiki-agent: MIT). ### Where can I find alternatives to agentset or llm-wiki-agent? GraphCanon lists graph-backed alternatives at [agentset alternatives](/tools/agentset-ai-agentset/alternatives) and [llm-wiki-agent alternatives](/tools/samuraigpt-llm-wiki-agent/alternatives) ([agentset markdown twin](/tools/agentset-ai-agentset/alternatives.md), [llm-wiki-agent markdown twin](/tools/samuraigpt-llm-wiki-agent/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/agentset-ai-agentset-vs-samuraigpt-llm-wiki-agent.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentset or llm-wiki-agent? agentset: Steady. llm-wiki-agent: 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 agentset and llm-wiki-agent? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentset trust report](/tools/agentset-ai-agentset/trust); [llm-wiki-agent trust report](/tools/samuraigpt-llm-wiki-agent/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agentset-ai-agentset`](/api/graphcanon/graph?tool=agentset-ai-agentset) - 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/_