get_api_operationList public REST API operations, or pass one (e.g. "POST /api/v1/query") for its parameters, request body, responses, and auth. Sourced from the published OpenAPI spec.
| Name | Required | Description | Default |
|---|---|---|---|
| operation | No | Operation key like "POST /api/v1/query"; omit to list all operations |
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 indicate read-only, idempotent, and non-destructive behavior. The description reinforces this by stating it 'lists' or 'passes one' for details, with no side effects mentioned. It also adds context that data comes from the OpenAPI spec, enhancing transparency without contradicting annotations.
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 two sentences to convey the full functionality. It is well-structured, front-loading the primary action (list or detail) and then adding the source. No unnecessary words or redundancy.
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 simple tool, the description provides all necessary context: the action (list/detail), the parameter format, the type of information returned, and the data source. It is self-contained and sufficient for an agent to decide when and how to use it.
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 'operation' has a clear description explaining the expected format (e.g., 'POST /api/v1/query') and the behavior when omitted (list all). This fully covers the parameter's meaning and usage, with 100% schema coverage.
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's purpose: listing all public REST API operations or providing detailed information (parameters, request body, responses, auth) for a specific operation. It also mentions the source (OpenAPI spec), leaving no ambiguity about what the tool does.
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 an example of how to specify an operation but does not explicitly differentiate when to use this tool versus the sibling tools (e.g., compare_storage_tiers, get_pricing). It implies usage for API operation lookups, but a direct comparison or condition for selection is missing.
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 have clearly distinct purposes: search, read, API reference, quickstart, formats, benchmarks. The main overlap is between compare_storage_tiers and get_pricing, which both cover storage-tier pricing and could confuse an agent.
The set mostly follows a predictable get_/list_/read_/search_ verb pattern with snake_case throughout. Minor deviation: read_doc and search_docs use navigation verbs instead of get_/list_, but the pattern remains readable.
Eight tools is well-scoped for a documentation-focused server. Each tool covers a meaningful documentation need without redundancy or bloat.
The surface covers the full documentation workflow: searching docs, reading docs, quickstart, API operations, pricing, storage tiers, formats, and benchmarks. No obvious dead ends or missing core operations.