An MCP server that enforces fail-closed deterministic checks, independent refute-first review, and tamper-evident hash-chained receipts for AI agent outputs before claiming completion.
An MCP server that enforces a scientific-method loop for AI-driven machine learning experiments, with hypothesis gating, diagnostics, and data forensics.
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.
MCP server that enforces governance on agentic decisions with auditable evidence records, providing tools for understanding, calibrating confidence, and navigating handoffs based on policy.
A backend MCP server that enables AI agents to publish, validate, and search research papers, submit swarm-compute jobs, and invoke formal proof checking on the P2PCLAW decentralized network.
An MCP server that enforces hard quality gates on AI coding agents, including forced web search, planning, and empirical test execution, to prevent common failure modes and ensure production-grade code.