TabuPulse AI: Autonomous Tabular Prediction Agent & MCP Server for Micro-SaaS & Freelancers

This submission is for the Hacktoberfest Open-Source AI Challenge: Week 2. The project, TabuPulse AI, is an Autonomous Tabular Prediction Agent and MCP Server designed for micro-SaaS and freelancers. Freelancers and micro-SaaS founders often have valuable tabular business records like Stripe exports, invoice payment logs, customer activity metrics, and support ticket queues.

However, they frequently face two major revenue killers: payment delays and customer churn. Traditional Machine Learning methods require extensive data cleaning, cross-validation, and hyperparameter tuning, while closed LLMs like GPT-4 and Claude often produce inaccurate results and expensive token fees. TabuPulse AI addresses these issues by combining Prior Labs TabPFN-3.5, a foundation model pre-trained on millions of synthetic datasets, with an Autonomous Revenue Agent and a Model Context Protocol (MCP) Server.

This allows TabuPulse to ingest raw tabular data, infer schema, select target variables, run Bayesian zero-shot predictions, quantify monetary capital at risk, and generate an Autonomous Revenue Action Playbook for founders to execute in one click. The system also exposes tools over MCP, enabling various AI agents to invoke TabPFN predictions directly.

The source code is available on GitHub, and the project is licensed under MIT. During development, TabuPulse was beta-tested by an independent web consultant managing multiple client retainers, who reported significant revenue protection benefits from the tool.