A sophisticated MCP server that provides a multi-dimensional, adaptive reasoning framework for AI assistants, replacing linear reasoning with a graph-based architecture for more nuanced cognitive processes.
An MCP server that enhances sequential thinking with meta-cognitive capabilities including confidence tracking, hypothesis testing, and organized memory storage through graph-based libraries and structured JSON documents.
A scientific reasoning framework that leverages graph structures and the Model Context Protocol (MCP) to process complex scientific queries through an Advanced Scientific Reasoning Graph-of-Thoughts (ASR-GoT) approach.
A multi-graph memory MCP server that traces cause-effect chains across semantic, entity, temporal, and causal graphs to answer 'why' questions with confidence-scored paths, enabling agents to reason beyond simple similarity retrieval.
An MCP server that provides standardized access to biomedical knowledge bases and resources, enabling AI systems to retrieve verified information from sources like bioRxiv, EuropePMC, and various protein/gene databases.
An MCP server that provides a self-improving knowledge graph with per-triple provenance and deterministic reasoning, enabling auditable, reproducible, and contradiction-aware answers for AI agents.
