القائمة
Manage Databricks workspace connections: check which workspace you're connected to, switch workspaces, list available workspaces, or authenticate to a new workspace.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | databricks-config |
| description | Manage Databricks workspace connections: check which workspace you're connected to, switch workspaces, list available workspaces, or authenticate to a new workspace. |
Use the manage_workspace MCP tool for all workspace operations. Do NOT edit ~/.databrickscfg, use Bash, or use the Databricks CLI.
Call ToolSearch with query select:mcp__databricks__manage_workspace to load the tool.
Map user intent to action:
action="status"action="list"list first to find the profile name, then action="switch", profile="<name>" (or host="<url>" if a URL was given)action="login", host="<url>"Call mcp__databricks__manage_workspace with the action and any parameters.
Present the result. For status/switch/login: show host, profile, username. For list: formatted table with the active profile marked.
Note: The switch is session-scoped — it resets on MCP server restart. For permanent profile setup, use
databricks auth login -p <profile>and update~/.databrickscfgwithcluster_idorserverless_compute_id = auto.
Builds Python-based Databricks applications using Dash, Streamlit, Gradio, Flask, FastAPI, or Reflex. Handles OAuth authorization (app and user auth), app resources, SQL warehouse and Lakebase connectivity, model serving integration, and deployment. Use when building Python web apps, dashboards, ML demos, or REST APIs for Databricks, or when the user mentions Streamlit, Dash, Gradio, Flask, FastAPI, Reflex, or Databricks app.
Create and query Databricks Genie Spaces for natural language SQL exploration. Use when building Genie Spaces or asking questions via the Genie Conversation API.
Parse documents (PDF, DOCX, PPTX, images) using ai_parse_document, or build custom RAG pipelines. Use when the user asks to parse documents or build a custom RAG.
Creates, configures, and updates Databricks Lakeflow Spark Declarative Pipelines (SDP/LDP) using serverless compute. Handles streaming tables, materialized views, CDC, SCD Type 2, and Auto Loader ingestion patterns. Use when building data pipelines, working with Delta Live Tables, ingesting streaming data, implementing change data capture, or when the user mentions SDP, LDP, DLT, Lakeflow pipelines, streaming tables, or bronze/silver/gold medallion architectures.
Generate realistic synthetic data using Spark + Faker (strongly recommended). Supports serverless execution, multiple output formats (Parquet/JSON/CSV/Delta), and scales from thousands to millions of rows. For small datasets (<10K rows), can optionally generate locally and upload to volumes. Use when user mentions 'synthetic data', 'test data', 'generate data', 'demo dataset', 'Faker', or 'sample data'.
Unity Catalog system tables and volumes. Use when querying system tables (audit, lineage, billing) or working with volume file operations (upload, download, list files in /Volumes/).