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srgplus-mcp

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by srgplus
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Python
Hybrid

list_workspaces

Read-only

Retrieve all workspaces accessible with the current API keys, returning IDs and names for selecting a workspace in other operations.

Instructions

List all workspaces accessible with the current API key(s).

Returns a SLIM row per workspace — id and name — which is all you need to
pick a workspace_id for other tools. For full details (seats, subscription,
hub profiles) call get_workspace(workspace_id); for a workspace's brands
call list_hub_profiles(workspace_id).

A user-level key (srgplus_u_) returns every workspace it can reach; multiple
keys are merged. The list comes from the single bulk call made when the key
was resolved, so it is one response, not one request per workspace.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.18

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already indicate read-only and non-destructive, but the description adds transparency by specifying the response format ('SLIM row' with id and name), the bulk-call nature, and behavior with user-level keys and merging multiple keys. This goes beyond the annotations.

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?

The description is well-structured and not overly long, but it includes some redundancy in the final sentence about the bulk call (already implied earlier). Still, it is front-loaded and concise enough for a tool with no parameters.

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

Completeness5/5

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

With no parameters and an output schema present, the description fully covers what an agent needs: it explains the purpose, the minimal return fields, and the relationship to other tools. Nothing critical is missing.

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?

No parameters exist in the schema, and the description does not need to explain any. Per the rubric, with 100% schema coverage, baseline is 3. The description adds no parameter-specific information because there are none.

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

Purpose5/5

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

Clear statement: 'List all workspaces accessible with the current API key(s).' It uses the specific verb 'List' with a clear resource and scope, and differentiates from sibling tools like get_workspace and list_hub_profiles.

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

Usage Guidelines5/5

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

Explicitly tells when to use: 'to pick a workspace_id for other tools', and contrasts with get_workspace for full details and list_hub_profiles for brands. The bulk-call behavior is also explained, providing clear context for when this tool is appropriate.

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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