A graph-based MCP server that provides AI coding agents with persistent memory to store patterns, track complex relationships, and retrieve knowledge across sessions. It leverages graph structures to handle temporal queries and relational paths that traditional vector stores often miss.
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.
GPU-accelerated graph visualization and analytics server for Large Language Models that integrates with Model Control Protocol (MCP), enabling AI assistants to visualize and analyze complex network data.
An MCP server that provides a shared graph of an organization's projects, processes, areas, and principles, enabling consistent context for tools and AI agents.
A model-neutral cyber capability brain for AI agents and human researchers, providing MCP tools for knowledge ingestion, composition, campaign planning, fleet management, evidence binding, and discovery replay.
Enables AI-native statistical analysis and reproducible research workflows through MCP, including natural language planning, protocol-based analysis, Python/R cross-validation, and publication-ready figure generation.
