get_environment_pinsList which version each environment currently pins for this spec, whether the pin is frozen, and where it came from. Requires project context.
| Name | Required | Description | Default |
|---|---|---|---|
| specId | Yes | Public ID (GUID) of the API specification |
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 description indicates a read-only operation ('List') and the annotations confirm readOnlyHint=true. No side effects are implied, and the description adds detail about the returned information. It does not mention error conditions or permissions, but the read-only nature is clearly conveyed.
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 concise, using a single sentence to state the action, the output fields, and the prerequisite. No redundant or filler content is present.
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?
There is no output schema, so the description appropriately summarizes the return data (version, frozen status, origin). It does not elaborate on domain terms like 'frozen,' but the scope is narrow and the description is sufficient for an agent to decide whether to call the tool.
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 single parameter specId is fully described in the schema as 'Public ID (GUID) of the API specification.' The description does not add extra meaning beyond the schema, but the schema itself provides sufficient clarity. With 100% parameter coverage, a score of 4 is appropriate.
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 'List' and the specific resource: version pins per environment for a spec. It also enumerates the output attributes (version, frozen status, origin), leaving no ambiguity about the tool's purpose.
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 notes 'Requires project context,' which is an important prerequisite for invoking the tool. It implies the tool should be used after setting context, though it does not explicitly contrast with alternative getter tools. This is adequate guidance for typical usage.
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.