by Eronred · MCP Server · ★ 1.5k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
ASO & App Marketing Skills AI agent skills for App Store Optimization (ASO) and mobile app marketing. Built for indie developers, app marketers, and growth teams who want Cursor, Claude Code, or any Agent Skills-compatible AI assistant to help with keyword research, metadata optimization, competitor analysis, market intelligence, and app growth. Powered by real App Store data via the Appeeky API. A web version is also available, powered by LLMs and our MCP:Appeeky Web. Why This Exists Most ASO knowledge lives in blog posts, courses, and expensive consultants. We packaged it into skills that any AI agent can use — so you get expert-level ASO guidance directly in your IDE. Each skill contains battle-tested frameworks, scoring rubrics, and output templates. The agent reads the skill, pulls real data from the App Store (via Appeeky), and gives you actionabl
| Stars | 1,513 |
| Forks | 98 |
| Language | Shell |
| Category | MCP Server |
| License | MIT |
| Quality Score | 57.854/100 |
| Last Updated | 2026-06-20 |
| Created | 2026-02-27 |
| Platforms | claude-code, cli, mcp |
| Est. Tokens | ~12k |
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aso-skills is AI agent skills for App Store Optimization (ASO) and app marketing. Built for indie developers, app marketers, and growth teams who want Cursor, Claude Code, or any Agent Skills-compatible AI assistan. It is categorized as a MCP Server with 1.5k GitHub stars.
aso-skills is primarily written in Shell. It covers topics such as app-store-analytics, app-store-connect, app-store-live.
You can find installation instructions and usage details in the aso-skills GitHub repository at github.com/Eronred/aso-skills. The project has 1.5k stars and 98 forks, indicating an active community.
aso-skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to aso-skills on Agent Skills Hub include app-store-screenshots, mcp-server-chart, EverMemOS. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.