Neurosymbolic AI combines symbolic reasoning, exemplified by Prolog, with neural networks’ pattern recognition to address their limitations and leverage their strengths. The integration of Prolog-style reasoning with deep learning in modern systems allows for better generalization and precise logical semantics. Prolog-MCP Server is a neurosymbolic AI backend that combines Prolog’s symbolic reasoning with the Model Context Protocol, providing tools for validating outputs, maintaining knowledge bases, and integrating neural and symbolic reasoning in AI workflows. The server can be efficiently deployed in serverless and Kubernetes environments, offering near-instant cold starts, high density, and security through WASI sandboxing.