Provides AI coding agents with five intelligence layers (dependency graph, git history, documentation, architectural decisions, code health) via nine MCP tools, enabling deep codebase understanding and reducing exploration cost.
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.
Enables AI agents to locally search, query, and understand codebases with token-efficient context, dependency graphs, history, architecture diagrams, and metrics through MCP.
Enables AI coding agents to query code structure efficiently through 16 MCP tools, including symbol lookup, full-text search, dependency analysis, and refactor planning, powered by tree-sitter parsing and index-backed code intelligence.
Enables AI coding assistants to semantically search and retrieve relevant code patterns, documentation, and implementations from a codebase via MCP tools.