list_response_componentsList the reusable response 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?
The read-only nature is consistent with the readOnlyHint annotation and the 'List' verb. The description adds the behavioral requirement that project context must be set, which is useful operational context beyond the annotation.
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 brief and front-loaded, with the primary purpose in the first sentence and a practical tip about an optional parameter in the second. The 'Requires project context' note is a concise, useful addition.
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 straightforward list operation with three parameters and no output schema, the description covers the essential prerequisites and parameter behavior. It does not mention pagination or return format, but these are not critical for a simple list tool and are likely absent from the schema anyway.
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?
All three parameters have clear descriptions in the schema (100% coverage), so the description adds little beyond restating includeUsageCounts behavior. The baseline of 3 applies because the schema fully documents each parameter's meaning.
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 action ('List'), the resource ('reusable response components'), and the scope ('of a spec version'). This effectively distinguishes it from related sibling tools that list shared responses or other component types.
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 includes a useful hint about the includeUsageCounts parameter and notes that project context is required, but it does not explicitly explain when to choose this tool over alternatives like list_shared_responses or get_response_component. This leaves the agent to infer the appropriate use case.
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.