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Query codebase knowledge graphs directly for faster, lower-token code understanding.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "PruvaGraph MCP Server" yet — see the docs or source repo.
Use PruvaGraph to query this codebase knowledge graph and summarize the architecture, core modules, main dependencies, and key entry files.
A concise overview of the project structure, module relationships, and key files with responsibilities.
Use PruvaGraph to find the modules, functions, and call chains related to user authentication and authorization, and tell me which files to read first.
A list of relevant code locations, call-chain paths, and a recommended reading order.
I plan to change the order status transition logic. Use PruvaGraph to analyze affected modules, upstream and downstream dependencies, and potential risk points.
An impact analysis with dependency nodes and the areas that need the most careful validation.
Query code structure and cross-language relationships via MCP with auditable access logs.
Turn codebases into structural graphs for efficient AI-assisted code exploration.
Index codebases into a searchable graph for structure, calls, and routes.
Provide structured code context and dependency graphs for efficient codebase understanding.
Gives AI coding agents repository intelligence, dependency analysis, and impact insights.
Provide code review, fixes, testing, and refactoring help in Claude Code.