MCP server for manufacturing defect investigation using knowledge graphs and graph analytics. Enables LLM agents to retrieve context, find similar cases, and generate investigation reports from manufacturing data.
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.
Transforms code repositories and development documentation into a queryable Neo4j knowledge graph, enabling AI assistants to perform intelligent code analysis, dependency mapping, impact assessment, and automated documentation generation across 15+ programming languages.
Enables storage and retrieval of knowledge in a graph database format, allowing users to create, update, search, and delete entities and relationships in a Neo4j-powered knowledge graph through natural language.
Enables enterprise document retrieval using graph-based reasoning and knowledge graphs. Allows agents to search and extract information from scattered documents through structured entity and relationship extraction.
Enables creating, managing, analyzing, and visualizing knowledge graphs with support for multiple graph types (topology, timelines, changelogs, requirements, knowledge bases, ontologies) including node/edge management and resource association.
