--- title: "openakita vs Agent-Reach" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/openakita-openakita-vs-panniantong-agent-reach" tools: ["openakita-openakita", "panniantong-agent-reach"] --- # openakita vs Agent-Reach *GraphCanon updated Jul 15, 2026* ## Verdict Pick openakita when license: openakita is AGPL-3.0, Agent-Reach is MIT; pick Agent-Reach when license: Agent-Reach is MIT, openakita is AGPL-3.0. [openakita](http://openakita.ai) reports 1.8k GitHub stars, 262 forks, and 55 open issues, last pushed Jul 15, 2026. [Agent-Reach](https://github.com/Panniantong/Agent-Reach) has 55k stars, 4.5k forks, and 144 open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [openakita's repository](https://github.com/openakita/openakita) and [Agent-Reach's repository](https://github.com/Panniantong/Agent-Reach). | | [openakita](/tools/openakita-openakita.md) | [Agent-Reach](/tools/panniantong-agent-reach.md) | | --- | --- | --- | | Tagline | An open-source AI assistant framework with skills and agent architecture | AI Agent for Automated Web and Social Media Data Extraction | | Stars | 1,843 | 54,715 | | Forks | 262 | 4,509 | | Open issues | 55 | 144 | | Language | Python | Python | | Adopt for | - | Agent-Reach facilitates hands-off web and social media scraping via command line with no API costs for retrieving varied internet content. | | Persona | - | - | | Runtime | - | - | | License | AGPL-3.0 | MIT | | Categories | AI Agents | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [openakita](/tools/openakita-openakita.md) | [Agent-Reach](/tools/panniantong-agent-reach.md) | | --- | --- | --- | | Open issues (now) | 55 | 144 | | Full report | [trust report](/tools/openakita-openakita/trust.md) | [trust report](/tools/panniantong-agent-reach/trust.md) | ## Decision facts: Agent-Reach - **Adopt for:** Agent-Reach facilitates hands-off web and social media scraping via command line with no API costs for retrieving varied internet content. ## Choose when ### Choose openakita if… - License: openakita is AGPL-3.0, Agent-Reach is MIT. - Tags unique to openakita: agent, ai, assistant, claw. - More recently updated (last pushed Jul 15, 2026). ### Choose Agent-Reach if… - License: Agent-Reach is MIT, openakita is AGPL-3.0. - Tags unique to Agent-Reach: agent-infrastructure, ai-agent, ai-search, bilibili. - Also covers Data & Retrieval. - When needing to bypass costly API fees for extensive social media platform data extraction ## When NOT to use openakita - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. ## When NOT to use Agent-Reach - If strict compliance with website scraping policies is critical due to its use of scraping techniques - When direct interaction through APIs for precision and reliability is preferred over scraping ## Common questions ### What is the difference between openakita and Agent-Reach? openakita: An open-source AI assistant framework with skills and agent architecture. Agent-Reach: AI Agent for Automated Web and Social Media Data Extraction. See the comparison table for live GitHub stats and shared categories. ### When should I choose openakita over Agent-Reach? Choose openakita over Agent-Reach when License: openakita is AGPL-3.0, Agent-Reach is MIT; Tags unique to openakita: agent, ai, assistant, claw; More recently updated (last pushed Jul 15, 2026). ### When should I choose Agent-Reach over openakita? Choose Agent-Reach over openakita when License: Agent-Reach is MIT, openakita is AGPL-3.0; Tags unique to Agent-Reach: agent-infrastructure, ai-agent, ai-search, bilibili; Also covers Data & Retrieval; When needing to bypass costly API fees for extensive social media platform data extraction. ### When should I avoid openakita? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. ### When should I avoid Agent-Reach? If strict compliance with website scraping policies is critical due to its use of scraping techniques When direct interaction through APIs for precision and reliability is preferred over scraping ### Is openakita or Agent-Reach more popular on GitHub? Agent-Reach has more GitHub stars (54,715 vs 1,843). Stars measure visibility, not whether either tool fits your constraints. ### Are openakita and Agent-Reach open source? Yes - both are open-source projects on GitHub (openakita: AGPL-3.0, Agent-Reach: MIT). ### Where can I find alternatives to openakita or Agent-Reach? GraphCanon lists graph-backed alternatives at [openakita alternatives](/tools/openakita-openakita/alternatives) and [Agent-Reach alternatives](/tools/panniantong-agent-reach/alternatives) ([openakita markdown twin](/tools/openakita-openakita/alternatives.md), [Agent-Reach markdown twin](/tools/panniantong-agent-reach/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/openakita-openakita-vs-panniantong-agent-reach.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, openakita or Agent-Reach? openakita: Very active. Agent-Reach: 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 openakita and Agent-Reach? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [openakita trust report](/tools/openakita-openakita/trust); [Agent-Reach trust report](/tools/panniantong-agent-reach/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=openakita-openakita`](/api/graphcanon/graph?tool=openakita-openakita) - 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/_