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Databricks Unity Catalog MCP Server

Databricks Unity Catalog MCP Server

by revodatanl

get-catalogs

Retrieves a list of all available catalogs in a Databricks workspace, helping you discover and select data sources for queries and metadata inspection.

Instructions

Retrieve a list of all available catalogs in the Databricks workspace

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
errorYes
contentYes
successYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must carry the behavioral burden; "Retrieve" weakly signals a read-only, non-mutating operation. It does not mention permissions/authentication requirements, whether results are paginated or capped, or that access is limited to catalogs the caller can see, though the existence of an output schema removes the need to describe the return shape.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no filler or redundant restatement of the name. It is efficient, though "available" is slightly imprecise about visibility scoping.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter read-only listing tool with an output schema already documenting returns, the description covers the essentials: what is listed and where. Minor gaps are the lack of hierarchy context and any mention of permissions or result limits.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so there is no parameter semantics to explain; the description correctly does not invent any. Baseline for a no-parameter tool applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Retrieve a list of all available catalogs") and scopes it to "the Databricks workspace". It is clear what is returned, but it never contrasts itself with hierarchical siblings such as get-schemas-in-catalogs or get-tables-in-catalogs-schemas, so the agent must infer the catalog/schema/table layering.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit when-to-use guidance, no prerequisites, and no named alternative. The only hint is "all available", which implies an unfiltered top-level listing, leaving the agent to infer that this is the entry point before descending into schemas and tables.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.