An MCP server that leverages graph structures to perform sophisticated scientific reasoning through an 8-stage processing pipeline, enabling AI systems to handle complex scientific queries with dynamic confidence scoring.
A framework for building and querying temporally-aware knowledge graphs that allows AI assistants to interact with graph capabilities through the Model Context Protocol.
An MCP-based multi-agent retrieval-augmented generation system that enables question answering over academic papers with hybrid search, knowledge graph multi-hop reasoning, and source-cited answers.
MCP server that integrates a 1200-paper RAG database with six tools to support research workflows across stages like hypothesis, experiment, statistics, and writing. It routes requests to specialized skills and real-time frontier searches to provide evidence-grounded research mentoring.
