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ChrisChoTW

databricks-mcp

by ChrisChoTW
OverviewSchemaRelated ServersScoreDiscussions
Python

list_workspace

Browse Databricks workspace directories to view files and folders. Specify a path to list contents for workspace navigation and organization.

Instructions

List Workspace directory contents

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNo/

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • tools/compute.py:110-114 (handler)
    The list_workspace function is defined here, decorated with @mcp.tool, and implements the logic to list workspace directory contents using a workspace client.
    @mcp.tool
def list_workspace(ctx: Context, path: str = "/") -> List[Dict[str, Any]]:
    """List Workspace directory contents"""
    w = get_workspace_client()
    return [obj.as_dict() for obj in w.workspace.list(path)]

Tool Definition Quality

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 the full burden of behavioral disclosure. It only states the basic action without mentioning permissions needed, whether it's read-only, pagination behavior, rate limits, or what the output looks like. 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 extremely concise—just four words—and front-loaded with the core action. There's no wasted language, 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 that there's an output schema (which reduces the need to describe return values) but no annotations and minimal parameter coverage, the description is incomplete. It covers the basic purpose but lacks behavioral and usage context needed for effective tool selection and invocation.

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?

The description doesn't mention any parameters, but the input schema has one parameter 'path' with 0% description coverage. Since there's only one parameter and the description doesn't add any semantic context, it meets the baseline of 3 for minimal parameter documentation, but doesn't compensate for the lack of schema coverage.

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 'List Workspace directory contents' clearly states the action (list) and resource (workspace directory contents), but it's somewhat vague about what 'workspace directory' specifically refers to in the Databricks context. It doesn't differentiate from sibling tools like 'list_volumes' or 'list_tables', which might also list workspace-related items.

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 tools like 'list_catalogs', 'list_schemas', and 'list_tables' that might list related resources, there's no indication of scope, hierarchy, or prerequisites for using this tool.

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

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