list_parameter_componentsList the reusable parameter components of a spec version. Set includeUsageCounts to see how often each one is referenced. Requires project context.
| Name | Required | Description | Default |
|---|---|---|---|
| specId | Yes | Public ID (GUID) of the API specification | |
| versionId | No | Optional version ID (GUID) to filter by a specific version | |
| includeUsageCounts | No | Also return how often each component is referenced (default false) |
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 readOnlyHint=true, so the read-only nature is covered. The description adds the requirement for project context and hints at the includeUsageCounts parameter behavior, but does not disclose return format, pagination, error conditions, or what happens without project context. This adds some value beyond annotations but leaves significant behavioral gaps.
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 two concise sentences with zero wasted words. The primary purpose is front-loaded, and the additional hint about includeUsageCounts and the prerequisite are compact. This is an efficient, well-structured description.
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?
For a list operation with three documented parameters and a readOnlyHint, the description covers the core action but lacks details on return format, pagination, or project context specifics. Since there is no output schema and the tool's behavior beyond listing is not described, an agent might be uncertain about expected response shape or limitations. Adequate but incomplete.
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?
Schema coverage is 100%, so all three parameters have descriptions. The description adds minimal meaning beyond the schema—it reiterates the includeUsageCounts purpose ('to see how often each one is referenced') and mentions project context as a non-parameter prerequisite. With high schema coverage, baseline 3 is appropriate; no extra parameter semantics are needed.
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 verb and resource: 'List the reusable parameter components of a spec version.' This distinguishes it from sibling list_*_component tools by specifying 'parameter components' and 'spec version.' However, it does not explicitly differentiate from get_parameter_component or list_shared_component_usages, though the plural 'list' and 'reusable' hint at scope.
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 only mentions a prerequisite ('Requires project context') and does not provide any guidance on when to use this tool over alternatives like list_header_components or get_parameter_component. No exclusions or conditions for selection are given, leaving the agent to infer usage from the name alone.
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.
The tools are mostly distinct with clear descriptions. Some pairs like get_header_policies vs get_resolved_headers or get_environment_verification vs get_monitoring_sync_status could be slightly confusing, but the descriptions clarify scope and purpose.
All tools follow a consistent snake_case verb_noun pattern (get_, list_, create_, update_, manage_, etc.). Even the few bare verbs like 'search' and 'set_context' are consistent with the naming scheme.
With 165 tools, the server is extremely heavy. This far exceeds the 'too many' threshold of 25+, making it difficult for an agent to navigate and select the right tool efficiently.
The tool surface covers a very broad API lifecycle domain: specs, environments, test cases, monitors, mock servers, security, governance, documentation, and team management. Read and write operations are present across most areas, with no obvious missing core functionality.