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Analyze project architecture and detect similar code patterns for cross-language consistency.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "MCP Project Guard" yet — see the docs or source repo.
Analyze this repository containing Java, Python, and Go services. Identify architectural layers, repeated feature implementations, and whether naming, error handling, and logging patterns are consistent. Then provide standardization recommendations.
A project architecture overview, a list of similar code patterns, inconsistency findings, and actionable standardization recommendations.
I want to add a new user authentication module. Scan the project for existing authentication, authorization, middleware, or request validation code, find the closest implementation patterns, and explain which structures and conventions should be reused.
Returns the most relevant reference code locations, pattern summaries, and structural and coding guidance for the new module.
Review the code added in this branch against existing repository patterns. Point out files with architectural deviations, duplicated implementations, or styles that do not follow team conventions, and rank them by severity.
Generates a severity-ranked issue list with matching reference implementations and suggested fixes.
Manage project architecture, modules, and data flows locally with full privacy.
Manage project analysis, code metrics, Git, docs, and files with natural language.
Connect GitHub repos so AI can analyze and build from real code.
Give AI coding agents filesystem, Git, database, and compute tools via MCP.
Analyze, match, and transform code structures across multiple programming languages.
Analyze code structure and Git history while drastically reducing AI token usage.