{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/a3b712f4442f40c6a01dd923d26c1a11\" frameborder=\"0\" width=\"1662\" height=\"1246\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1246,"width":1662,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1246,"thumbnail_width":1662,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/a3b712f4442f40c6a01dd923d26c1a11-5e19c39634028b52.gif","duration":198.513,"title":"Connect Databricks Vector Search to Thunk 😃","description":"I show an example of connecting Databricks VectorSearch to Thunk. In Databricks, I use a customer review dataset and a VectorSearchIndex with full text and embedding search, then copy the MCP server URL from the compute VectorSearch page. In Thunk, I add a custom connection named Review Search, paste the MCP server URL, and enter my Databricks personal access token as a bearer authorization header. After adding it, I test the tool by searching for oatmeal and confirm results return with vector search scores. I then enable the tool in my workflow and update the instructions to use it for related review search."}