Query the current state of any in-flight async operation by operation_id.
WHEN TO USE: Use to poll the state of a pending_async operation when no webhook callback has arrived or to check progress. WHEN NOT TO USE: Do not poll more frequently than once per 10 seconds — use webhook delivery for real-time updates instead. COST: free - no key required LATENCY: ~50ms
| Name | Required | Description | Default |
|---|---|---|---|
| operation_id | Yes |
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 provide readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds valuable behavioral context: it mentions latency (~50ms), cost (free), and the nature of the operation (polling for in-flight async ops). It does not contradict annotations. While it doesn't detail response structure, the description goes beyond annotations by adding usage constraints and performance characteristics.
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 and logically structured with headers. The primary purpose is stated first, followed by usage guidelines, cost, and latency. Every sentence provides actionable information without redundancy or filler.
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?
Given the tool's simplicity (single parameter, no nested objects, no output schema), the description provides sufficient context for an agent to use it correctly. It covers when to use, constraints, and operational characteristics. The only minor gap is the lack of explicit mention of what response fields to expect, but since it's a status query and the description names the resource, agents can reasonably infer it returns status information. Overall, it's highly complete for a polling 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 input schema has no description for operation_id (0% coverage), so the description must compensate. It explicitly states that operation_id identifies the async operation, which adds meaning beyond the schema's type-only definition. Since there is only one parameter and its purpose is clear, the description adequately compensates for the low 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: 'Query the current state of any in-flight async operation by operation_id.' It uses a specific verb (query) and resource (state of async operation) with a clear parameter. This distinguishes it from sibling tools like get_outcome which likely deals with different data, and it is not a tautology.
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?
Explicitly provides 'WHEN TO USE' and 'WHEN NOT TO USE' sections. It advises polling for pending operations and warns against excessive polling ('Do not poll more frequently than once per 10 seconds'), suggesting webhook delivery for real-time updates. This gives clear conditions and alternatives, which is exemplary guidance.
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 differentiated targets (e.g., check_booking_link vs import_booking_url, get_status vs get_outcome), and the descriptions are unusually thorough. However, send_message and send_transactional_confirmation overlap because send_message already includes a 'transactional' message type, and verify_business vs verify_company_record are easy to confuse despite different scopes.
All 23 tools use a consistent verb_noun snake_case pattern (check_*, get_*, send_*, verify_*), with no camelCase or stylistic drift. The verb uniformly precedes the object, making the surface predictable and easy to navigate.
23 tools is on the heavy side for a single MCP server, spanning SMB communications, booking, compliance screening, trade lookup, and platform utilities. Each tool has a purpose, but the count pushes the set into the 16-25 borderline range and suggests scope creep.
Core workflows for booking, messaging, and compliance pre-flight are well covered, including async polling and cost preview. However, there are lifecycle gaps: capture_lead has no way to list/update/retrieve leads, and business records support import/verify but no update/delete. The trade/company-verification tools also feel disconnected from the main SMB flow.