An MCP code-intelligence server for AI agents with pre-indexed AST cache, 62 MCP tools, and TOON-compressed output, enabling token-efficient code analysis and project health grading entirely locally.
Provides AI agents with a live architecture model of a codebase, enabling queries for root cause analysis, blast radius, and dependency traversal through MCP tools.
Provides AI assistants with a structured, token-efficient map of a codebase's symbols, dependencies, and relationships via MCP tools like overview, query, and impact analysis.
Provides AI agents with a function-level dependency graph of the codebase through 30 MCP tools, enabling structural queries about code dependencies, callers, and impact analysis.
Provides code intelligence for AI coding agents by indexing repositories into a hybrid knowledge graph, enabling agents to query dependencies, impact, and context through 28 MCP tools.
Provides AI-powered architecture analysis and visualization of codebases, exposing 17 MCP tools for querying components, dependencies, and generating interactive diagrams.
Enables AI agents to locally search, query, and understand codebases with token-efficient context, dependency graphs, history, architecture diagrams, and metrics through MCP.