About this project
What it does: LogicLens is an automated argument analysis engine that transforms complex, unstructured academic text into visual logic graphs. Using the Model Context Protocol (MCP), it enables researchers to automatically extract claims and evidence, map their relationships, and perform algorithmic audits to detect logical fallacies like circular reasoning and isolated claims. Who it is for: It is designed for university students, academic researchers, and peer reviewers who need to rapidly synthesize large volumes of literature and ensure the logical integrity of their arguments before publication or submission. What makes it special: Unlike static annotation tools, LogicLens is a protocol-native, interoperable engine. It doesn't just "highlight" text; it performs deep-graph traversal to mathematically validate reasoning chains. By exposing these insights through standard MCP tools and resources, it integrates seamlessly into any research workflow, providing a rigorous, automated "logic health check" that enhances the quality of scholarly work.
Education & Research track
Build innovative tools that transform learning, teaching, academic research, and knowledge discovery.