New cookbook - Supply-Chain Copilot with OpenAI Agent SDK and Databricks MCP Servers (#1935)

This walkthrough demonstrates how to build a supply‑chain copilot using the OpenAI Agent SDK and Databricks Managed MCP, highlighting Tracing, Guardrails, and seamless integration with enterprise data sources. It shows how an agent can blend structured inventory tables, forecasting models, graph‑based BOM logic, vector‑indexed e‑mails behind a single conversational interface, then surface the results through FastAPI and a React chat UI. Readers learn to authenticate against Databricks, expose Unity Catalog functions and Vector Search (Databricks vector index) as MCP tools, trace every call in the OpenAI dashboard, and enforce guardrails, all while keeping the underlying data governance intact.

Author: lara-openai

authors.yaml

@@ -377,6 +377,11 @@ alexl-oai:
   website: "https://www.linkedin.com/in/alex-lowden01/"
   avatar: "https://avatars.githubusercontent.com/u/215167546"
 
+lara-openai:
+  name: "Lara Rachidi"
+  website: "https://www.linkedin.com/in/lara-rachidi/"
+  avatar: "https://avatars.githubusercontent.com/u/208707651?v=4"
+
 glojain:
   name: "Glory Jain"
   website: "https://www.linkedin.com/in/gloryjain/"

examples/mcp/databricks_mcp_cookbook.ipynb

@@ -45,6 +45,18 @@
     - functions
     - tracing
 
+- title: Building a Supply-Chain Copilot with OpenAI Agent SDK and Databricks MCP Servers
+  path: examples/mcp/mcp_tool_guide.ipynb
+  date: 2025-07-08
+  authors:
+    - lara-openai
+  tags:
+    - agents
+    - mcp
+    - vector-search
+    - supply-chain
+    - databricks
+
 - title: Eval Driven System Design - From Prototype to Production
   path: examples/partners/eval_driven_system_design/receipt_inspection.ipynb
   date: 2025-06-02