An in-memory knowledge graph MCP server that gives coding agents structural and semantic recall over codebases by indexing Python source, ADR documents, and project configuration, exposing 7 tools for search, traversal, context retrieval, and natural-language Q&A.
A local knowledge graph MCP server that provides AI agents with permanent, structured memory about codebases, enabling semantic search, blast radius analysis, and convention enforcement.
Local repository intelligence MCP server that builds a reusable graph of code structure for AI coding agents, providing 34 network-free tools for understanding, searching, and analyzing repositories without data leaving the machine.
AI-native code intelligence graph that builds a persistent knowledge graph of your codebase in Neo4j and exposes it to AI assistants via MCP, enabling contextual code analysis, impact analysis, and dependency tracking.
Local-first MCP server that scans a repository once and answers architecture questions from an evidence-backed graph, enabling dependency analysis, impact analysis, and codebase exploration without re-reading the source tree.
