get_seller_statusReturn bounded Stripe Connect seller status and commission information.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| mode | Yes | ||
| canSell | Yes | ||
| country | Yes | ||
| currency | Yes | ||
| connected | Yes | ||
| nextSteps | Yes | ||
| commissionBps | Yes | ||
| chargesEnabled | Yes | ||
| payoutsEnabled | Yes | ||
| detailsSubmitted | Yes | ||
| standardCommissionBps | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare this as a safe, read-only, idempotent operation, so the description does not need to repeat those traits. It adds the term 'bounded' and clarifies the returned content is Stripe Connect seller status and commission info, but 'bounded' is vague and no additional behavioral context like data freshness or access requirements is provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence with no filler. However, the word 'bounded' is ambiguous and could confuse an agent, preventing a perfect score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With zero parameters, an output schema present, and annotations covering safety and idempotency, the description is mostly sufficient for invoking the tool. It lacks richer context about what 'bounded' means or how the status relates to Stripe Connect onboarding, but the available structured metadata compensates for most gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and an empty schema, so the baseline is 4. There are no parameter semantics for the description to clarify, and nothing in the description contradicts or complicates the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns seller status and commission information for Stripe Connect, using a specific verb and resource. It does not explicitly differentiate itself from related siblings like create_stripe_onboarding_session or list_seller_sales, but the resource scope is clear enough for basic identification.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool versus alternatives, nor does it mention prerequisites such as whether a seller account must already be onboarded. Usage context is only implied by the tool name and description, so an agent has to infer when this is the right call.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target a distinct resource and action, and lifecycle pairs like publish_note_listing vs publish_media_listing or get_note vs get_collaboration_note are separated by clear wording. A few near-pairs such as move_file vs move_workspace_item and trash_file vs trash_workspace_item could still cause an agent to pick the wrong tool without careful reading.
All 38 tools follow one consistent verb_noun snake_case pattern with no camelCase or mixed conventions. Even less common verbs like upsert, trash, purge, and validate are applied uniformly, making the tool set predictable.
38 tools is well above the 25+ threshold and makes the overall surface feel heavy for tool selection. The number is defensible given the broad workspace, collaboration, and marketplace scope, but as a single MCP server it is not especially well-scoped.
The tool set covers workspace content lifecycle, collaboration, public pages, marketplace listings, Stripe seller flow, and agent registration without major dead ends. Minor gaps exist, such as no permanent delete outside of the trash flow and no direct collaboration-note deletion, but core workflows are supported.