apihub_get_service
Get full details for a specific API service including all endpoints, schemas, and pricing.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| service_slug | Yes | The service slug (e.g., 'exchange-rates') |
mcp-server
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
A3.8/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. It states what the tool returns (endpoints, schemas, pricing), which adds useful behavioral context. However, it does not disclose potential side effects, authentication requirements, rate limits, or error conditions. Since this is a read operation, the omission of side effects might be acceptable, but the description could be richer.
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, well-structured sentence that front-loads the verb and object. It lists three concrete content categories without wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema), the description sufficiently informs the agent of the return content and the need for a specific service. It could mention that the service_slug must be a valid slug, but that is implied by the schema. Overall, it is complete for a getter tool.
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 100%: the only parameter service_slug has a description with an example. The description does not add any additional meaning beyond the schema, so it meets the baseline of 3.
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?
The description clearly states the verb 'Get' and the resource 'full details for a specific API service', specifically listing endpoints, schemas, and pricing. This distinguishes it from siblings like apihub_list_services, which would list services rather than retrieve a single service.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: you call this tool when you need full details for a particular API service. However, it does not explicitly mention alternatives or when not to use it (e.g., 'use apihub_list_services to browse services'). The context is clear but exclusions are absent.
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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TDQS
A4.2/5.0
Disambiguation5/5
Each tool has a clearly distinct role: balance check, service discovery (list/search), service details, paid calls (onboarded vs external vs content), and credit top-up. The similar pairs (search vs search_external, call vs call_external) are separated by onboarded vs external scope, and descriptions explicitly guide selection.
Naming Consistency4/5
All names share the 'apihub_' prefix and use snake_case, with verbs like get, list, search, call, read. However, 'balance' and 'topup' deviate from the verb_noun pattern, making the convention slightly inconsistent but still predictable and readable.
Tool Count5/5
With 9 tools, the set is well-scoped for a credit-based API marketplace. Each tool serves a distinct step in the workflow (discover, inspect, call, manage funds), with no redundant tools and nothing missing at the broad level.
Completeness4/5
The surface covers the full lifecycle: searching and listing services, retrieving details, making calls to both onboarded and external APIs, reading content, checking balance, and topping up credits. Minor gaps like transaction history or service ratings exist but do not hinder the core purpose.