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Check Japanese UI typography, forms, honorifics, and JLReq compliance for AI agents.
The available material is very limited, but based on known facts, this MCP tool requires no secrets, declares no remote endpoints, and is listed in an official registry with open-source code, so the overall risk appears relatively low. The main caution is that it is an executable MCP tool with local code-execution capability, while documentation and license information are sparse, limiting audit visibility.
The material explicitly states that no keys or environment variables are required. No API tokens, account credentials, or other highly sensitive secrets are mentioned, so credential leakage and abuse risk appears low.
No remote host endpoints are declared, and the material does not show that user data is sent to external services. Based on the available information, there is no clear outbound data path.
System checks indicate that this tool executes code/processes, which is a normal high-privilege capability for MCP tools and warrants caution regarding local execution scope. However, the material does not show any abnormal system permissions beyond its stated purpose.
The description suggests it performs Japanese UI/UX checks for AI coding agents, which typically implies access to local code, UI text, or form content. The material does not define precise read/write boundaries, so the actual scope of project data access should be reviewed.
Positive factors include the official registry source, an auditable open-source repository, and updates within the last year. However, the missing README, undeclared license, and very low community adoption (0 stars) limit supply-chain transparency and external validation, so source and dependency review is advisable before use.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "io.github.mrslbt/japan-ux" MCP server from askskill: Run: claude mcp add 'io-github-mrslbt-japan-ux' -- npx -y japan-ux-mcp
Review this Japanese signup form UI/UX for Japanese user expectations. Focus on field labels, required markers, error messages, button copy, honorific language, and JLReq typography rules: Name, Furigana, Email Address, Password, Confirm Password.
A checklist of issues plus more natural, compliant Japanese UI copy and layout suggestions.
Review the honorifics and tone consistency in the following Japanese product UI copy. Identify unnatural, overly polite, or contextually inappropriate phrasing and suggest alternatives: ログインしてください、会員登録をお願いします、情報を入力して頂けますでしょうか。
Tone issues, recommended replacement copy, and notes on when each phrasing fits best.
Audit this page design against Japanese UI/UX and JLReq rules. Check punctuation spacing, line length, line breaks, mixed full-width and half-width characters, spacing between numbers and units, and button/label readability. List all fixes needed.
A list of typography issues, the relevant guideline basis, and actionable UI fixes.
Find Japanese e-Gov law revisions and diff legal text by history ID.
Make AI coding agents production-ready with quality and readiness checks.
Enable AI agents to process Japanese calendar, address, names, and corporate IDs.
Query Japanese laws and ordinances in natural language through the e-Gov Law API.
Quickly find Japanese NLP libraries, corpora, dictionaries, and LLM resources.
Query Japanese public data via official APIs with normalized English metadata.