context-protocol

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.

Paradigm is a procedural learning and trust layer for AI agents. It learns from validated deliberative decisions, compiles stable behaviors into specialized reflexes, and keeps uncertain or unsupported states on the deliberative path.

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

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

Sovereign context, memory and provenance infrastructure for AI agents. Bitemporal knowledge, evidence and decision lineage, delivered to any agent over the EPCTX/1 protocol (SDK/REST/MCP). Local-first, zero-egress, no mandatory LLM. MIT.

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

An MCP server that delegates mechanical code edits to a cheap worker model, validates them through a chain of gates, and applies them atomically. Supports PHP & Python.