3 posts tagged with "MCP"

In Part 1 we extracted a BW system's metadata into a single DuckDB file with erpl-adt catalog sync — 53 cubes, 226 queries, every characteristic and key figure, all the lineage between them. Browsable, searchable, and completely decoupled from SAP.

Now we do the interesting thing. We unplug.

No SAP credentials in this post. No VPN, no connection, no --host. Just catalog.duckdb — the file from Part 1 — and an AI agent. The goal: take one cube (0D_NW_C01, "Actual for NW Demo") and its flagship query (0D_FC_NW_C01_Q0008, "YTD Sales by Sales Org") and reverse-engineer them into runnable dbt models on DuckDB. Reconstruct the star schema, the measures, and the year-to-date logic — from metadata alone, offline.

Here is exactly how it went.

← Part 1: Your SAP Data Is Already Real-Time

In Part 1, a mid-size manufacturer's forecasting team got a live, validated, DuckDB-native view of their SAP order and customer data — fresh within five minutes, anomalies caught at the gate, no warehouse in the middle.

This post is Part 2. It answers the next two questions: how does the AI agent actually reach that data, and what happens when the data is wrong?

The short version: we publish the view as a REST endpoint and an MCP tool with flAPI so the agent can call it, and when the agent finds a bad number it reads the ABAP behind the view, writes a patch, and files a transport with erpl-adt.

We built erpl-adt because we got tired of Eclipse being the only way to interact with ABAP systems programmatically. If you wanted to search objects, read source code, or run unit tests against SAP — you had to use Eclipse ADT. No CLI, no scriptable API client, nothing you could plug into a CI pipeline or hand to an AI agent.

So we built one. A single binary that speaks the ADT REST API, works from the command line, and doubles as an MCP server for AI coding agents.