PUG UK & Ireland Conference 2026

Implementing MCP Servers with OpenEdge 

The Model Context Protocol (MCP) is an emerging standard for connecting AI agents and large language models with tools and enterprise systems. In this talk, we focused on the OpenEdge MCP Server, introduce the core concepts of MCP, and discussed general use cases for integrating OpenEdge applications with AI-based workflows. The session covered building an MCP server based on existing OpenEdge business logic, enabling AI-driven processes to both retrieve data from OpenEdge applications and invoke transactional logic to update data. With the availability of the Progress MCP Connector and MCP Server for OpenEdge, this integration has become significantly easier. Typical scenarios include exposing OpenEdge data to AI assistants or chatbots, supporting natural-language access to business data, and integrating OpenEdge systems into user- and customer-facing AI workflows.

ModernAIzing OpenEdge Applications Through Structured Refactoring  with the SmartComponent Library  

Modernizing OpenEdge applications requires more than adding new interfaces or technologies - it starts with structured refactoring of the existing ABL codebase. This session shows how legacy OpenEdge systems can be systematically refactored to enable modern architectures while preserving existing business logic.

Using the SmartComponent Library as a full-stack framework, the talk demonstrated practical refactoring approaches: identifying modernization candidates, decoupling legacy structures, introducing clear architectural boundaries, and enabling REST-based integration and modern web frontends. Modern tooling, including AI-assisted analysis and refactoring support, helps accelerate code understanding and identify suitable refactoring paths within large ABL codebases.

The focus remained on controlled, architecture-driven refactoring. The session highlighted where AI can effectively support modernization tasks - and where human architectural decisions remain essential to ensure predictable, sustainable results.