dbx-mcp
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- AlicenseNot gradedqualityCmaintenanceEnables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.1GPL 3.0
TDQS
Scored across 45 tools
Most tools have clearly distinct resource targets (clusters, warehouses, pipelines, UC, Vector Search, Lakebase), and detailed descriptions clarify action scopes. A few pairs overlap, such as manage_sql_warehouse vs manage_warehouse, and list_compute duplicates listing functionality found in resource-specific tools, so occasional misselection is possible.
All names use snake_case with a consistent verb_noun/manage_noun pattern across the large tool set. Abbreviations (ka, mas, uc, vs) are used consistently within families, though some names rely on them and one tool is noun-only (list_compute).
45 tools exceeds the 25+ threshold for being too many, which creates a large surface for agents to search and select from. Even though each tool multiplexes many actions and Databricks is a broad platform, the count is well beyond a comfortably scoped server.
The surface covers broad Databricks lifecycle operations across jobs, pipelines, UC objects/grants/tags, Vector Search, Lakebase, volumes, and workspace files. Minor gaps remain, such as secrets, repos, and user/group management, but most core workflows can be completed or worked around.