Enables decomposition of complex research queries into multi-hop sub-queries and synthesis DAGs, with scientific consensus analysis, citation credibility verification, and deterministic JSON outputs for MCP-compliant clients.
Transforms AI assistants into research-grade cognitive workspaces with systematic reasoning, evidence-based analysis, persistent memory management, and intelligent knowledge discovery.
Enables autonomous multi-study scientific paper analysis, consensus ratio calculation, citation credibility verification, and multi-hop research queries through the Model Context Protocol.
Enables scientific literature research through multi-agent search, analysis, and semantic memory, exposing 9 MCP tools for querying, storing, and retrieving research findings.
