databricks-mcp

by ChrisChoTW

Overview Schema Source Related Servers Discussions Admin

Python

list_warehouses

Retrieve a list of available SQL warehouses for querying data and managing analytics workloads in Databricks.

Instructions

List SQL Warehouses

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_warehouses"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
`result`	Yes

Implementation Reference

tools/compute.py:84-87 (handler)
The handler function `list_warehouses` that lists Databricks SQL Warehouses. Note that while the @mcp.tool decorator appears to be missing for this specific function in the provided code, it is intended to be an MCP tool.
```
def list_warehouses(ctx: Context) -> List[Dict[str, Any]]:
    """List SQL Warehouses"""
    w = get_workspace_client()
    return [wh.as_dict() for wh in w.warehouses.list()]
```

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Mar 17, 2026

TDQS

B3.2/5.0

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 for behavioral disclosure. 'List SQL Warehouses' implies a read-only operation, but it doesn't specify any behavioral traits like pagination, rate limits, authentication requirements, or what the output contains. For a tool with zero annotation coverage, this is insufficient.

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, efficient phrase ('List SQL Warehouses') that directly states the purpose with zero wasted words. 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 the tool's simplicity (0 parameters, output schema exists), the description is minimally adequate. However, with no annotations and many sibling tools, it lacks context about when to use it and behavioral details. The output schema handles return values, but the description doesn't provide enough guidance for an agent to use it effectively in context.

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 input schema has 0 parameters with 100% description coverage, so no parameter documentation is needed. The description doesn't add parameter information, which is appropriate here. A baseline of 4 is given for tools with zero parameters, as there's nothing to compensate for.

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?

The description clearly states the verb ('List') and resource ('SQL Warehouses'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its many sibling list tools (e.g., list_catalogs, list_clusters, list_tables), which all follow the same 'List [resource]' pattern, so it misses full sibling differentiation.

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?

The description provides no guidance on when to use this tool versus alternatives. With many sibling list tools available, there's no indication of what distinguishes SQL Warehouses from other resources or when this specific listing is appropriate. No exclusions or prerequisites are mentioned.

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