$ loading_
Turn any LLM into a codebase expert with search, mapping, and security insights.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "code-context-mcp" yet — see the docs or source repo.
Search this codebase for the core modules related to user authentication and authorization, explain their responsibilities and call relationships, and list the files I should read first.
A map of auth-related code locations, module explanations, dependencies, and a recommended reading order.
Analyze the overall architecture of this project, describe the relationships among frontend, backend, data storage, and external services, and summarize key design patterns and main entry points.
A structured architecture overview with component relationships, key entry points, design patterns, and system boundaries.
Review this codebase for potential security issues, focusing on input validation, authorization bypass, sensitive data exposure, and dependency risks, then provide remediation suggestions.
A list of potential vulnerabilities, affected locations, risk explanations, and actionable fixes.
Search and navigate multiple code repositories with natural language understanding.
Search repositories semantically and turn codebases into AI-ready context and knowledge.
Analyze codebases with semantic search, dependency insights, and natural language Q&A.
Search codebases semantically and find relevant snippets with source locations.
Explore codebases faster with context-aware search and fuzzy snippet matching.
Analyze code structure and Git history while drastically reducing AI token usage.