--- title: "oh-my-openagent vs semble" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/code-yeongyu-oh-my-openagent-vs-minishlab-semble" tools: ["code-yeongyu-oh-my-openagent", "minishlab-semble"] --- # oh-my-openagent vs semble *GraphCanon updated Jul 12, 2026* ## Verdict Pick oh-my-openagent if decisive facts about oh-my-openagent; pick semble if semble is a Python-based tool that facilitates fast and accurate code search for AI agents with up to 98% fewer tokens compared to traditional grep+read methods. [oh-my-openagent](https://omo.dev) reports 66k GitHub stars, 5.3k forks, and 876 open issues, last pushed Jul 11, 2026. [semble](https://minish.ai/packages/semble/introduction/) has 5.6k stars, 236 forks, and 8 open issues, last pushed Jul 8, 2026. Figures are from public GitHub metadata via [oh-my-openagent's repository](https://github.com/code-yeongyu/oh-my-openagent) and [semble's repository](https://github.com/MinishLab/semble). | | [oh-my-openagent](/tools/code-yeongyu-oh-my-openagent.md) | [semble](/tools/minishlab-semble.md) | | --- | --- | --- | | Tagline | A coding agent for complex codebases, supporting multiple AI agents like ChatGPT and Claude. | Fast and Accurate Code Search for Agents | | Stars | 65,526 | 5,581 | | Forks | 5,344 | 236 | | Open issues | 876 | 8 | | Language | TypeScript | Python | | Adopt for | Decisive facts about oh-my-openagent. | Semble is a Python-based tool that facilitates fast and accurate code search for AI agents with up to 98% fewer tokens compared to traditional grep+read methods. | | Persona | - | - | | Runtime | - | - | | License | Other | MIT | | Categories | AI Agents, Developer Tools | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [oh-my-openagent](/tools/code-yeongyu-oh-my-openagent.md) | [semble](/tools/minishlab-semble.md) | | --- | --- | --- | | Days since push | 0d | 3d | | Open issues (now) | 876 | 8 | | Owner type | User | Organization | | Security scan | No lockfile | No MCP manifest | | Full report | [trust report](/tools/code-yeongyu-oh-my-openagent/trust.md) | [trust report](/tools/minishlab-semble/trust.md) | ## Decision facts: oh-my-openagent - **Adopt for:** Decisive facts about oh-my-openagent. ## Decision facts: semble - **Requirements:** Operating with Python, Semble does not require Docker for its operation. - **Adopt for:** Semble is a Python-based tool that facilitates fast and accurate code search for AI agents with up to 98% fewer tokens compared to traditional grep+read methods. ## Choose when ### Choose oh-my-openagent if… - oh-my-openagent is primarily TypeScript; semble is Python. - License: oh-my-openagent is Other, semble is MIT. - Tags unique to oh-my-openagent: ai, codex, chatgpt, claude. - Also covers Developer Tools. - oh-my-openagent ships an MCP server manifest. - When working with complex codebases and requiring integration with multiple AI systems like Anthropic, ChatGPT, and Claude for better code orchestration and lifecycle hook management. ### Choose semble if… - semble is primarily Python; oh-my-openagent is TypeScript. - License: semble is MIT, oh-my-openagent is Other. - Requirements: Operating with Python, Semble does not require Docker for its operation.. - Tags unique to semble: embeddings, agents, retrieval, mcp. - Also covers Data & Retrieval. - - Use Semble when you are specifically working with AI agents or models and require efficient, token-economical code search operations. ## When NOT to use oh-my-openagent - When your project is not reliant on AI integration or complex orchestration capabilities. For simpler codebases, its advanced features may be overkill. - If your development environment does not support TypeScript or if you are exclusively working with Codex CLI and prefer a less integrated solution, opting for another tool could be more suitable since ## When NOT to use semble - - Avoid using Semble if your use case does not involve AI agents or the model-context-protocol (MCP). Competitor tools might offer better features tailored to non-agent-based code search. - - Not recommended in scenarios where token efficiency is not a concern, as competitors may provide more versatile functionalities without focusing on token reduction. ## Common questions ### What is the difference between oh-my-openagent and semble? oh-my-openagent: A coding agent for complex codebases, supporting multiple AI agents like ChatGPT and Claude.. semble: Fast and Accurate Code Search for Agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose oh-my-openagent over semble? Choose oh-my-openagent over semble when oh-my-openagent is primarily TypeScript; semble is Python; License: oh-my-openagent is Other, semble is MIT; Tags unique to oh-my-openagent: ai, codex, chatgpt, claude; Also covers Developer Tools; oh-my-openagent ships an MCP server manifest; When working with complex codebases and requiring integration with multiple AI systems like Anthropic, ChatGPT, and Claude for better code orchestration and lifecycle hook management. ### When should I choose semble over oh-my-openagent? Choose semble over oh-my-openagent when semble is primarily Python; oh-my-openagent is TypeScript; License: semble is MIT, oh-my-openagent is Other; Requirements: Operating with Python, Semble does not require Docker for its operation.; Tags unique to semble: embeddings, agents, retrieval, mcp; Also covers Data & Retrieval; - Use Semble when you are specifically working with AI agents or models and require efficient, token-economical code search operations. ### When should I avoid oh-my-openagent? When your project is not reliant on AI integration or complex orchestration capabilities. For simpler codebases, its advanced features may be overkill. If your development environment does not support TypeScript or if you are exclusively working with Codex CLI and prefer a less integrated solution, opting for another tool could be more suitable since ### When should I avoid semble? - Avoid using Semble if your use case does not involve AI agents or the model-context-protocol (MCP). Competitor tools might offer better features tailored to non-agent-based code search. - Not recommended in scenarios where token efficiency is not a concern, as competitors may provide more versatile functionalities without focusing on token reduction. ### Is oh-my-openagent or semble more popular on GitHub? oh-my-openagent has more GitHub stars (65,526 vs 5,581). Stars measure visibility, not whether either tool fits your constraints. ### Are oh-my-openagent and semble open source? Yes - both are open-source projects on GitHub (oh-my-openagent: Other, semble: MIT). ### Where can I find alternatives to oh-my-openagent or semble? GraphCanon lists graph-backed alternatives at [oh-my-openagent alternatives](/tools/code-yeongyu-oh-my-openagent/alternatives) and [semble alternatives](/tools/minishlab-semble/alternatives) ([oh-my-openagent markdown twin](/tools/code-yeongyu-oh-my-openagent/alternatives.md), [semble markdown twin](/tools/minishlab-semble/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/code-yeongyu-oh-my-openagent-vs-minishlab-semble.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, oh-my-openagent or semble? oh-my-openagent: Very active. semble: 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 oh-my-openagent and semble? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [oh-my-openagent trust report](/tools/code-yeongyu-oh-my-openagent/trust); [semble trust report](/tools/minishlab-semble/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=code-yeongyu-oh-my-openagent`](/api/graphcanon/graph?tool=code-yeongyu-oh-my-openagent) - 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/_