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 "blockers": [
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  "Add the keyless docs MCP at https://developers.databricks.com/api/mcp; it speaks MCP 2025-11-25, so start with initialize.",
  "Once a person has made the workspace, run 'databricks auth login' (OAuth U2M with a localhost:8020 callback) or use a PAT from 'databricks tokens create'."
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 "summary": "An agent can read Databricks' docs, REST reference and keyless docs MCP, and its email code arrives fast, but both the Free Edition and the trial sign-up stop at an Arkose Labs puzzle on 'Set up your account'. Without a workspace, no token, CLI login, API or MCP call was possible, so none of the ten core tasks could be driven.",
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    "cli": "databricks sql",
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   "check": "GET /api/2.0/sql/statements/{id} shows status SUCCEEDED with result rows",
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   "source": "https://www.databricks.com/product/databricks-sql",
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   "weight": "core",
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   "surfaces": {
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    "mcp": null,
    "cli": "databricks schemas create",
    "ui": "Catalog Explorer"
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   "check": "GET /api/2.1/unity-catalog/schemas/{name} returns the created schema",
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   "source": "https://www.databricks.com/product/unity-catalog",
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   "weight": "core",
   "plan": "paid",
   "surfaces": {
    "api": "POST /api/2.1/unity-catalog/tables",
    "mcp": null,
    "cli": "databricks tables create",
    "ui": "Catalog Explorer"
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   "check": "GET /api/2.1/unity-catalog/tables/{full_name} returns the table with its schema",
   "capability_id": "cap_ec6ajdnd",
   "unmapped": null,
   "source": "https://www.databricks.com/product/unity-catalog",
   "result": "blocked",
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  {
   "id": "cap-04",
   "capability": "Build and run an ETL pipeline (Lakeflow)",
   "weight": "core",
   "plan": "paid",
   "surfaces": {
    "api": "POST /api/2.0/pipelines",
    "mcp": null,
    "cli": "databricks pipelines create",
    "ui": "Lakeflow Pipelines UI"
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   "check": "GET /api/2.0/pipelines/{id} shows the pipeline with a completed update",
   "capability_id": "cap_xb7x9h8v",
   "unmapped": null,
   "source": "https://www.databricks.com/product/data-engineering",
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   "id": "cap-05",
   "capability": "Orchestrate jobs/workflows on a schedule or trigger",
   "weight": "core",
   "plan": "paid",
   "surfaces": {
    "api": "POST /api/2.2/jobs/create",
    "mcp": null,
    "cli": "databricks jobs create",
    "ui": "Workflows UI"
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   "check": "GET /api/2.2/jobs/runs/get shows run state SUCCESS",
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   "source": "https://www.databricks.com/product/data-engineering/lakeflow-jobs",
   "result": "blocked",
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  {
   "id": "cap-06",
   "capability": "Ingest data from a source into the lakehouse (Lakeflow Connect)",
   "weight": "core",
   "plan": "paid",
   "surfaces": {
    "api": "POST /api/2.0/pipelines (ingestion pipeline)",
    "mcp": null,
    "cli": "databricks pipelines create",
    "ui": "Lakeflow Connect UI"
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   "check": "Querying the destination table shows newly landed source rows",
   "capability_id": "cap_yr6whrah",
   "unmapped": null,
   "source": "https://www.databricks.com/product/data-engineering/lakeflow-connect",
   "result": "blocked",
   "via": "api"
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  {
   "id": "cap-07",
   "capability": "Deploy a model or AI agent as a serving endpoint",
   "weight": "core",
   "plan": "paid",
   "surfaces": {
    "api": "POST /api/2.0/serving-endpoints",
    "mcp": null,
    "cli": "databricks serving-endpoints create",
    "ui": "Model Serving UI"
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   "check": "GET /api/2.0/serving-endpoints/{name} shows state READY",
   "capability_id": "cap_jzq3rf56",
   "unmapped": null,
   "source": "https://www.databricks.com/product/model-serving",
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  {
   "id": "cap-08",
   "capability": "Build a conversational analytics agent over data (Genie)",
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   "plan": "paid",
   "surfaces": {
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    "mcp": "Genie",
    "cli": null,
    "ui": "Genie space"
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   "check": "GET /api/2.0/genie/spaces/{id} returns the configured Genie space answering a sample question",
   "capability_id": "cap_79kc0h3h",
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   "source": "https://www.databricks.com/product/genie/one",
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  {
   "id": "cap-09",
   "capability": "Create an AI/BI dashboard over query data",
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   "plan": "paid",
   "surfaces": {
    "api": "POST /api/2.0/lakeview/dashboards",
    "mcp": null,
    "cli": null,
    "ui": "AI/BI Dashboards"
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   "check": "GET /api/2.0/lakeview/dashboards/{id} returns the published dashboard definition",
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   "source": "https://www.databricks.com/product/databricks-sql",
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   "id": "cap-10",
   "capability": "Run a vector search over embedded data (AI Search)",
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