databricks-mcp

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list_schemas

Retrieve all schemas within a specified Databricks catalog to organize and access database structures for querying and metadata exploration.

Instructions

List schemas in the specified catalog

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "catalog_name": "<catalog_name>"
    },
    "name": "list_schemas"
  }
}

Input Schema

Name	Required	Description	Default
`catalog_name`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Implementation Reference

tools/query.py:46-49 (handler)
The list_schemas function executes the "SHOW SCHEMAS IN {catalog}" SQL query to retrieve a list of schemas in a specific catalog, using safe_identifier to prevent SQL injection. It is registered as an MCP tool using the @mcp.tool decorator.
```
def list_schemas(ctx: Context, catalog_name: str) -> List[Dict[str, Any]]:
    """List schemas in the specified catalog"""
    catalog = safe_identifier(catalog_name, "catalog_name")
    return execute_sql(ctx, f"SHOW SCHEMAS IN {catalog}")
```

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Mar 17, 2026

TDQS

C2.8/5.0

Behavior2/5

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

No annotations are provided, so the description carries full burden. It discloses the basic action but lacks behavioral traits: no info on permissions required, rate limits, output format (though output schema exists), pagination, or error handling. This is inadequate for a tool with no annotation coverage.

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

Conciseness5/5

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

The description is a single, clear sentence with zero waste—it directly states the tool's function without fluff. It's appropriately sized and front-loaded, making it easy to parse quickly.

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

Completeness3/5

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

Given 1 parameter, no annotations, and an output schema, the description is minimally complete. It covers the basic purpose but lacks context on usage, behavior, and parameter details. The output schema mitigates the need to explain return values, but overall it's adequate with clear gaps.

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

Parameters3/5

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

Schema description coverage is 0%, so the description must compensate. It adds minimal semantics by specifying that 'catalog_name' is required and used to list schemas, but doesn't explain format, constraints, or examples. With 1 parameter and low coverage, this is a baseline score as it provides some context but not enough detail.

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

Purpose3/5

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

The description states the action ('List') and resource ('schemas'), but it's vague about scope—it doesn't specify if this lists all schemas, only active ones, or includes metadata. It distinguishes from siblings like 'list_tables' or 'get_table_schema' by focusing on schemas, but lacks specificity about what 'list' entails (e.g., pagination, filtering).

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?

No guidance on when to use this tool versus alternatives is provided. It doesn't mention prerequisites (e.g., needing catalog access), exclusions, or compare to siblings like 'list_catalogs' or 'get_table_schema'. The agent must infer usage from the name alone.

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