The Audited Context Generation (ACG) Protocol prevents AI hallucinations with a dual-layer system. The UGVP layer links every fact to a precise source for verification. The RSVP layer audits the AI's logical reasoning when combining facts. This creates a fully transparent, machine-auditable trail for both source and logical integrity.

Local MCP server for batch analysis of .als files without needing to open the DAW. Extract project metadata to identify missing samples, audit plugin usage, find duplicate projects, etc. w/ structural hashing.

📝 Enhance your Markdown workflow with this MCP server, designed for structured editing and full compliance with MCP 2025 standards.

🛠️ Enhance RAG systems with ACG to reduce hallucinations in LLM responses by improving accuracy and grounding in reliable external knowledge.

A lightweight Model Context Protocol (MCP) server that provides a bridge between Claude AI and a local Python environment.

Finance-ops RAG agent over two sources — real SEC EDGAR filings and FP&A planning documents — with answers grounded in retrieved passages, citations to the exact section, and a refusal when out-of-corpus. Demonstrates an end-to-end RAG pipeline, token minimization, and MCP-server retrieval tools. Built on public SEC data plus synthetic FP&A docs.