An MCP server that provides structural codebase indexing and surgical query tools to drastically reduce token usage through symbol-level searches and transitive impact analysis. It supports multiple languages and integrates with git to help AI agents understand code dependencies and the impact of changes in sub-millisecond time.
MCP server that builds a dependency graph of your codebase, giving AI agents structural understanding to analyze impact, find context, and make safe modifications across languages and infrastructure.
MCP server that builds a local code intelligence layer, letting AI agents explore call graphs, blast radius, and source slices via a single tool without external APIs.
An MCP server that provides ultra-efficient code exploration through AST analysis, reducing LLM token usage by up to 95% while enabling instant call graph generation and dependency analysis for massive codebases.
MCP server that exposes pre-extracted facts about code behavior, design decisions, and assumptions to AI agents, saving time and tokens by avoiding direct source file reading.
An MCP server that extracts complete knowledge from any codebase — architecture, patterns, dependencies, API surface. Combines static analysis with AI-powered deep interpretation.
