Use this guide to create a context repo from catalog assets, review the generated files, publish a version, and make it available to another tool.Documentation Index
Fetch the complete documentation index at: https://docs.sidecardata.com/llms.txt
Use this file to discover all available pages before exploring further.
Before you start
You need:- A Sidecar workspace with Context Garage enabled
- A connected warehouse with catalog assets synced into Sidecar
- Permission to create and publish context repos
Create a context repo
Select assets
Choose the Catalog tables this repo should track. You can select individual tables or select a broader database or schema scope.To include matching tables that are discovered later, enable Future for the selected scope.

Choose sync behavior
Click Next: Sync behavior. Choose whether Sidecar should auto-apply Catalog drift to tracked repo files.When Metadata sync is enabled, Sidecar can update the draft for column adds and removals, type changes, table deletions, and description updates. You can override this behavior later inside the repo.

Name the repo
Click Next: Name & create. Enter a repo name and optional description.The description appears on the repo card and inside the Build view.

Review and edit files
Use the file navigator to open generated files and review the YAML. Common first edits include:- Update dataset and field descriptions
- Mark important fields as dimensions, facts, or time dimensions
- Add relationships between datasets
- Add shared metrics

Publish a version
When the draft is ready, publish it.Review generated artifacts
Review the generated OSI and target-specific artifacts, such as Cortex YAML.
Serve the published version
After publishing, choose how to use the version.Download YAML
Download the generated OSI or target-specific YAML for a self-managed
workflow.
Serve through MCP
Create an MCP deploy surface and generate a token for AI tools that support
MCP.
Deploy to Snowflake Cortex
Create a Cortex deploy surface to push the generated semantic view YAML to
Snowflake.
Track latest
Configure a deploy surface to track the latest published version so new
versions are served automatically.

Keep the repo current
As your catalog changes, return to the asset selector to update what the repo tracks. When you save selection changes:- Newly selected tables are added to the draft
- Unselected tables are removed from the draft
- Existing dataset files remain in place
- Future inclusion rules continue to add matching new assets


