Project Synapse

This MCP server implements Project Synapse, an autonomous knowledge synthesis engine that combines Montague Grammar-based semantic parsing, Zettelkasten methodology, and Neo4j graph database storage to transform raw text into interconnected knowledge graphs and generate novel insights through pattern detection. Built using Python with spaCy, NetworkX, and scikit-learn, it provides tools for ingesting and semantically analyzing text, storing entities and relationships in Neo4j, exploring graph connections, and autonomously generating insights using community detection, centrality analysis, and semantic clustering algorithms. The implementation features formal semantic analysis with logical form generation, background insight processing, evidence-based validation with confidence scoring, and specialized prompts for knowledge synthesis workflows, making it valuable for research automation, knowledge management systems, and building AI assistants that need to discover non-obvious connections and patterns across large text corpora.