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ABAP Copilot Grounding and MCP Bridge

| Alice Vinogradova |

ABAP Copilot Vibe Coding

YouTube

Anchor

Spotify

Apple

Episode #250

Introduction

In episode 250 of our SAP on Azure video podcast we talk about ABAP Vibe Coding! Vibe coding is a very hot topic at the moment. I myself have explored a few things and the results using Claude or GitHub Copilot are atcually pretty impressive. When doing this with ABAP, the results are only so-so. From timt to time the LLM suggests function modules or data objects that actually do not exist in the SAP system. This can be quite frustrating. So wouldn’t it be great if there was a way to ground the LLM on the data objects that are actually available in MY SAP system? Well, I am glad to have Alice Vinogradova back with us to give us some sneek peak at what can happen if you combine the OData MCP Bridge, a custom OData service which exposes classes, interaces and functions and GitHub Copilot.

Find all the links mentioned here: https://www.saponazurepodcast.de/episode250

Reach out to us for any feedback / questions:

#Microsoft #SAP #Azure #SAPonAzure #GitHubCopilot #ABAP #VibeCoding #MCP

Summary created by AI

  • Holger announced that the current episode is Episode 250 of the SAP on Azure video podcast, scheduled for release on July 7th. He introduced Goran and Alice, who will discuss SAP and Microsoft-related topics, including wipe coding and the integration of Odata MCP bridge with GitHub Copilot.
    • Episode 250 Announcement: Holger announced that the current episode is Episode 250 of the SAP on Azure video podcast, scheduled for release on July 7th. He mentioned that another episode would be released the following Saturday, and this episode would be released the Saturday after that.
    • Introduction of Guests: Holger introduced Goran and Alice as the guests for the episode. He mentioned that they would discuss topics related to SAP and Microsoft, including wipe coding and the integration of Odata MCP bridge with GitHub Copilot.
  • Alice’s Background and Experience:
  • Alice shared her extensive experience as a senior software developer at Microsoft, with a focus on ABAP programming. She mentioned her recent project comparing SAP systems with the Z80 microprocessor, highlighting her passion for automation and optimization.
    • Professional Background: Alice detailed her professional background, mentioning that she has been a senior software developer at Microsoft for almost three years. She has a total of 23 years of experience in ABAP programming and 33 years in programming overall.
    • Early Career: Alice started her career in 2002 as an internal in-house developer. She began with Z80 microprocessor programming, which she has a strong affinity for due to its influence on her early career.
    • Recent Project: Alice discussed her recent project where she compared SAP systems with the Z80 microprocessor. This project was done for fun and to explore the potential of using optimizations from Z80 in modern ABAP programming.
    • Passion for Automation: Alice emphasized her passion for automation and optimization, which has been a driving force in her career. She mentioned that many of the optimizations she used in her recent project were inspired by her early work with the Z80 microprocessor.
  • Odata MCP Bridge Overview:
  • Alice explained the Odata MCP bridge, which connects diverse Odata services with MCP, enabling AI agents to access ERP systems like SAP, Oracle, and Dynamics. This bridge simplifies the process by providing a single layer to handle various business processes.
    • Bridge Functionality: Alice explained that the Odata MCP bridge connects diverse Odata services with MCP, allowing AI agents to access ERP systems such as SAP, Oracle, and Dynamics. This connection enables the agents to perform tasks within these systems.
    • Supported Systems: The bridge supports various ERP systems, including SAP, Oracle, Dynamics, Salesforce, and Workday. It allows AI agents to interact with these systems through Odata services.
    • Read-Only Mode: Alice mentioned that the bridge can operate in read-only mode to ensure that no data is altered or damaged during the interaction with the ERP systems. This mode provides a layer of security and prevents unintended changes.
    • Agentic Applications: The Odata MCP bridge is particularly useful for agentic applications in the AI community, as it provides the tools needed for AI agents to perform tasks within ERP systems. This capability is significant for developing sophisticated AI-driven business processes.
  • Grounding GitHub Copilot with SAP Data:
  • Holger and Alice discussed the challenges of using GitHub Copilot for ABAP programming due to hallucinations and invented function modules. Alice proposed grounding the code generation with actual data from the SAP system using the Odata MCP bridge, significantly reducing hallucinations and improving code quality.
    • Challenges with Copilot: Holger and Alice discussed the challenges faced when using GitHub Copilot for ABAP programming. They noted that the tool often hallucinated and invented function modules or classes that did not exist in the SAP system, leading to non-functional code.
    • Grounding with SAP Data: Alice proposed a solution to ground the code generation process with actual data from the SAP system using the Odata MCP bridge. This approach would ensure that the generated code is based on real data objects and functions available in the system.
    • Reduction of Hallucinations: By grounding the code generation with actual SAP data, the hallucinations and inaccuracies in the generated code would be significantly reduced. This improvement would lead to more reliable and functional ABAP code.
    • Implementation Steps: Alice explained the steps to implement this solution, including exposing Odata services that list programs, classes, interfaces, and function modules. These services would be used by GitHub Copilot to verify the existence of data objects before generating code.
  • Demonstration of MCP Bridge and GitHub Copilot:
  • Alice demonstrated the integration of the MCP bridge with GitHub Copilot, showing how it can access SAP system data to verify the existence of classes, function modules, and other elements. This integration helps generate accurate and context-aware code.
    • Integration Setup: Alice demonstrated the setup of the MCP bridge with GitHub Copilot, explaining how the bridge connects to the SAP system and exposes Odata services that list available classes, function modules, and other elements.
    • Verification Process: During the demonstration, Alice showed how GitHub Copilot uses the MCP bridge to verify the existence of classes and function modules in the SAP system before generating code. This verification process ensures that the generated code is accurate and context-aware.
    • Tool Configuration: Alice configured the tools in GitHub Copilot to use the MCP bridge, enabling the tool to access the SAP system data. She highlighted the importance of setting up the tools correctly to ensure seamless integration and accurate code generation.
    • Example Queries: Alice provided example queries to demonstrate how GitHub Copilot interacts with the SAP system through the MCP bridge. These queries included searching for classes, verifying their existence, and generating code based on the verified data.
  • Exploring LLM-Related Classes in SAP:
  • Alice used the MCP bridge to search for LLM-related classes in the SAP system, generating a list of interesting classes and their functionalities. This included classes for load balancing, parallel processing, token count prediction, and code completion.
    • Search Process: Alice demonstrated the process of using the MCP bridge to search for LLM-related classes in the SAP system. She initiated a query to find classes with “LLM” in their names and retrieved a list of relevant classes.
    • Class Functionalities: The search results included classes with functionalities such as load balancing, parallel processing, token count prediction, and code completion. Alice provided an overview of these functionalities and their significance in the context of LLMs.
    • Class Details: Alice explored the details of the retrieved classes, including their methods and parameters. She highlighted how these classes could be used to enhance LLM-related tasks within the SAP system.
  • Generating and Visualizing Code Flow:
  • Alice demonstrated the generation of a data flow graph for an LLM class using the MCP bridge and GitHub Copilot. The generated graph provided a visual representation of the control flow and data flow within the class.
    • Graph Generation: Alice demonstrated the process of generating a data flow graph for an LLM class using the MCP bridge and GitHub Copilot. She initiated a query to create the graph, which visually represented the control flow and data flow within the class.
    • Visualization Tools: Alice used visualization tools to render the generated graph. She highlighted the importance of visualizing the code flow to understand the interactions and dependencies within the class.
    • Graph Details: The generated graph included details such as method calls, data interactions, and control structures. Alice explained how these details provide insights into the class’s functionality and behavior.
  • Creating a Test Demo Program:
  • Alice attempted to create a test demo program using the MCP bridge and GitHub Copilot, showcasing the potential for automated code generation and validation within the SAP system. The process involved verifying the existence of classes and generating accurate code.
    • Program Creation: Alice demonstrated the process of creating a test demo program using the MCP bridge and GitHub Copilot. She initiated a query to generate the program, which involved verifying the existence of classes and generating accurate code based on the verified data.
    • Verification Steps: The process included steps to verify the existence of classes and function modules in the SAP system before generating the code. This verification ensured that the generated code was accurate and functional.
    • Code Generation: Alice showcased the generated code, explaining how it was created based on the verified data from the SAP system. She highlighted the accuracy and context-awareness of the generated code.
  • Future Plans and Improvements:
  • Alice and Holger discussed future plans for enhancing the MCP bridge and GitHub Copilot integration, including the ability to write code and perform more complex operations. They emphasized the goal of achieving full automation in ABAP programming.
    • Enhancement Plans: Alice and Holger discussed plans to enhance the MCP bridge and GitHub Copilot integration. These plans include adding the ability to write code and perform more complex operations within the SAP system.
    • Full Automation: The ultimate goal is to achieve full automation in ABAP programming. Alice and Holger emphasized the importance of automating repetitive tasks and improving the efficiency of the development process.
    • Implementation Steps: Alice outlined the steps needed to implement the planned enhancements, including developing new Odata services and refining the existing integration. These steps aim to improve the functionality and usability of the MCP bridge and GitHub Copilot.

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