Enables interaction with 20+ databases (PostgreSQL, MongoDB, Neo4j, Elasticsearch, Redis, and more) through a single unified interface, allowing cross-database queries and operations via natural language.
Enables building and querying code knowledge graphs for project analysis, with tools for exploring code relationships, managing workflows, and automating development tasks. Integrates with Git and GitHub for branch management and pull request creation.
Combines a knowledge graph with RAG (Retrieval-Augmented Generation) capabilities for semantic code indexing and search. Enables creating entity relationships, managing observations, and performing semantic searches across indexed codebases.
Enables semantic code search across multiple repositories using AST-aware chunking and relationship tracking. Supports local LLM embeddings, real-time indexing, and cross-codebase dependency analysis through vector and graph databases.
Enables AI agents to query and analyze code across multiple repositories through a unified knowledge graph, with tools for symbol search, impact analysis, and graph algorithms.
Ingests any GitHub repository's code into a Neo4j knowledge graph and exposes it as read-only MCP tools, enabling users to query repo structure, dependencies, and function details via natural language.
