Synapse
Transforms raw text into interconnected knowledge graphs and autonomously generates insights through advanced pattern detection.
About
Project Synapse is a revolutionary Model Context Protocol (MCP) server designed for autonomous knowledge synthesis and inference. It expertly transforms raw textual information into dynamic, interconnected knowledge graphs, leveraging formal semantic analysis (Montague Grammar) and the Zettelkasten methodology. This unique combination enables the autonomous generation of actionable insights through sophisticated pattern detection, fostering a true cognitive partnership between humans and AI.
Key Features
- Formal semantic analysis using Montague Grammar for precise meaning extraction and logical form generation.
- Interconnected knowledge storage and high-performance graph traversal with Neo4j.
- Autonomous insight generation and continuous learning via a Zettelkasten engine.
- Full MCP protocol compliance for seamless integration with Large Language Models (LLMs).
- Auditable reasoning trails and confidence scoring for all generated hypotheses.
- 2 GitHub stars
Use Cases
- Process and analyze raw text through a full semantic pipeline to build comprehensive knowledge graphs.
- Autonomously generate new insights and hypotheses by detecting patterns within stored knowledge.
- Query complex knowledge networks using natural language, prioritizing synthesized insights with complete reasoning trails.