Local-first MCP server for data quality that finds suspicious data, explains findings with evidence, tracks drift, and supports human-approved, reversible repair workflows. Deterministic by default, with AI optional.
Enables LLMs to perform statistical analysis and generate ML predictions on user data from databases or CSV files through a Model Context Protocol server.
A unified context layer that connects your local data — repositories, documents, remote machines, and notes — to LLM interfaces through the Model Context Protocol (MCP).
An MCP server that exposes GPU-accelerated anomaly detection to AI assistants via the Model Context Protocol. Provides two MCP tools: waveguard_scan (send training + test data in one call, returns per-sample anomaly scores and top explanatory features) and waveguard_health (check API and GPU status). Works on time series, JSON, numbers, text, and images — fully stateless.
Enables users to query enterprise sales data from a local SQLite database and investigate anomalies through an inline dashboard with human-in-the-loop review buttons.