Lakehouse cost commands

These examples assume an authenticated active saved profile with the intended organization and project. Confirm it with tp context show before running commands. Add root --json before the command when machine parsing needs JSON output; use root --profile <name> only to override the active profile. Use one route consistently. Both routes call the same ThinkPlatform backend and use the same org/project authorization.

CLI route

Run commands using the active saved profile:

tp profile show PROFILE
tp lakehouse costs overview \
  --from YYYY-MM-DD --to YYYY-MM-DD --scope project
tp lakehouse warehouses list
tp lakehouse query-history list \
  --from FROM_ISO --to TO_ISO --limit 200
tp lakehouse jobs list
tp lakehouse runs list --job-id JOB_ID --from ISO_START --to ISO_END --limit 20

Use --scope organization only as an org owner. Use --force-refresh only when stale provider data would materially affect the conclusion; it is not a routine refresh option. Do not enable query text during broad collection. Run the bounded collector:

tp-lakehouse-cost-snapshot --help

MCP route

Use these ThinkPlatform system tools in a managed Agent:

Intent	MCP system tool	CLI equivalent
Financial and usage overview	`databricks_get_cost_overview`	`tp lakehouse costs overview`
Warehouse state/config	`databricks_list_warehouses`	`tp lakehouse warehouses list`
Recent execution causes	`databricks_list_query_history`	`tp lakehouse query-history list`
Job definitions	`databricks_list_jobs`	`tp lakehouse jobs list`
Period-bounded Job runs	`databricks_list_job_runs` with `start_time_from`/`start_time_to`	`tp lakehouse runs list --from ... --to ...`
SQL preview	Databricks SQL preview system tool with `fresh=false`	`tp lakehouse sql preview`
Notebook run	Databricks notebook run system tool with `compute_mode`	`tp lakehouse notebooks run --compute ...`
Job upsert	Databricks Job upsert system tool with `compute_mode`	`tp lakehouse jobs upsert-* --compute ...`

Pass explicit cost/query dates and scope, and bound Job runs with start_time_from/start_time_to. Keep include_query_text=false. If a tool is missing, report that capability gap; do not bypass project boundaries with ad-hoc credentials.

Cost-aware operation examples

tp lakehouse sql preview \
  --query "SELECT key, metric FROM ${TP_DATABRICKS_CATALOG}.gold.metrics LIMIT 100"
tp lakehouse sql preview --file check.sql --fresh
tp lakehouse notebooks run notebooks/daily \
  --compute serverless --wait
tp lakehouse jobs upsert-notebook \
  --name daily --notebook-path notebooks/daily --compute serverless --dry-run

Preview uses the shared cache by default. Use --fresh only for an explicit new read. Prefer serverless; use job-cluster for unsupported workloads and existing-cluster only with an explicit cluster ID and authorization.

Targeted follow-up

Filter Query History by warehouse_id and status before increasing the limit.
Inspect runs only for ranked project Jobs; do not enumerate unrelated workspace Jobs.
Use SQL hash, duration, cache status, bytes/rows read, and status in reports. Retrieve raw SQL only when an org owner explicitly authorizes it and the diagnosis cannot proceed otherwise.

Get started

CLI

Python SDK

Agent skills

CLI route

MCP route

Cost-aware operation examples

Targeted follow-up

​CLI route

​MCP route

​Cost-aware operation examples

​Targeted follow-up

CLI route

MCP route

Cost-aware operation examples

Targeted follow-up