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Server Details
PRO Services Prices: the site's own MCP server — enquiry (enquiry = a human handoff, not a...
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
3 toolsenquiry_describeWhat you get: an ENQUIRY with a human (not a purchase, not a guaranteed quote)AInspect
Read first. States plainly what submit_enquiry does on PRO Services Prices: it starts an enquiry with human providers who quote directly. Nothing is bought, ordered or paid; no quote is guaranteed; it is free. Also returns who receives the details, the consent wording, and how the person confirms.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It openly states that nothing is bought/ordered/paid, no quote is guaranteed, and it is free. It also details what the tool returns (who receives details, consent wording, confirmation process). This is transparent about both the tool's own output and the underlying enquiry process.
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 sentences, front-loaded with the directive 'Read first.' Every phrase adds value: it states the purpose, the nature of the enquiry, key caveats, and the return content. There is no wasted wording, and the structure is efficient and clear.
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 meta-descriptive tool with no parameters and no output schema, the description is complete. It explains what the tool does, what it returns, and the context of the underlying submit_enquiry action. An agent can confidently use this tool to understand the enquiry flow without missing critical details.
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 tool has zero parameters, so schema coverage is trivially 100%. With no parameters to describe, the baseline score of 4 applies. The description does not need to add parameter information, and it correctly focuses on behavior and output instead.
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: it explains what submit_enquiry does on PRO Services Prices, distinguishing it from purchase/quote actions. It explicitly mentions the tool's output (who receives details, consent wording, confirmation method), making its role unambiguous. The title reinforces the purpose, and the 'Read first' instruction differentiates it from siblings.
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 opens with 'Read first,' which is an explicit directive on when to use this tool (before engaging with submit_enquiry). It does not directly mention alternatives like enquiry_fields, but the contrast with 'not a purchase, not a guaranteed quote' clarifies the context. The usage guidance is clear enough, though it could more explicitly state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
enquiry_fieldsThe questions the enquiry asksAInspect
Every field of the PRO Services Prices enquiry: key, label, type, whether required, help text and the allowed options where there are any. Pass answers to submit_enquiry keyed by field key.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It reveals what fields are returned but does not explicitly say the operation is read-only, has no side effects, or requires no auth. The zero-parameter design makes major risks unlikely, so this is adequate but not enriched.
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?
A single, tightly written sentence that front-loads the resource ('Every field of the PRO Services Prices enquiry'), enumerates the field attributes, and closes with a usage pointer. Every phrase adds value and there is no 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?
For a zero-parameter tool with no output schema, the description covers what is returned (key, label, type, required, help text, options) and how the result is meant to be used (keyed answer submission). It lacks an explicit statement of the response format, but for such a simple read-only listing this is a minor gap.
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 parameters, so the baseline is 4. The description adds useful semantic context by explaining that returned field keys are the same keys used to structure answers for submit_enquiry, which helps the agent connect the output to the next step even though there are no input parameters to document.
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 that the tool returns every field of the PRO Services Prices enquiry and enumerates what those fields contain (key, label, type, required, help text, allowed options). It does not use an explicit verb like 'list' or 'fetch', and it does not distinguish the tool from the sibling 'enquiry_describe', so it falls short of a 5.
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 implies how the output should be used by saying 'Pass answers to submit_enquiry keyed by field key', but it never directly states when to use this tool versus 'enquiry_describe' or 'submit_enquiry'. There is no explicit context about prerequisites or exclusion conditions, leaving the timing of use to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
submit_enquirySubmit an ENQUIRY to human providers (two steps; not a purchase)AInspect
Submits an enquiry to PRO Services Prices — NOT a purchase, NOT a guaranteed quote. Step 1: call with the answers (keyed by field key from enquiry_fields) and consent=true; it validates and returns a summary, the consent line and a confirmation token — show the person the summary and the consent line. Step 2: only if the person agrees, call again with the same answers, consent=true and the confirmation token; the enquiry is then submitted, and the person receives an email with a link they must click before any provider sees it. Consent means the person has read and agreed to: "Happy for my details to go to relevant UAE PRO service providers, who'll quote me directly."
| Name | Required | Description | Default |
|---|---|---|---|
| answers | Yes | the person's answers, keyed by field key | |
| consent | Yes | true only when the person has agreed to: Happy for my details to go to relevant UAE PRO service providers, who'll quote me directly. | |
| confirmation | No | the confirmation token from step 1, after the person has approved the summary |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations given, the description carries the full burden of behavioral disclosure. It explains that step 1 only validates and returns a summary/token, step 2 actually submits and triggers an email, and providers see the enquiry only after the person clicks the emailed link. It also defines consent with the exact wording.
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 a single dense paragraph but is logically organized by Step 1/Step 2 and front-loads the purpose before the procedure. Every sentence carries necessary information about workflow, consent, or side effects; no filler 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?
For a two-step tool with no output schema, the description fully explains inputs, outputs of each step, the consent requirement, and the downstream email-link behavior. An agent has everything needed to call step 1, relay the summary, and conditionally execute step 2.
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 schema already covers all three parameters (100% coverage), so the baseline is 3. The description adds step-specific meaning beyond the schema: answers are keyed from enquiry_fields, consent must be true in both calls, and confirmation is the token returned in step 1 that enables step 2.
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?
States a specific verb and resource ('Submits an enquiry to PRO Services Prices') and immediately clarifies what it is not ('NOT a purchase, NOT a guaranteed quote'). The title reinforces 'two steps; not a purchase,' and the reference to 'enquiry_fields' positions it relative to sibling tools. An agent can tell exactly what action this performs.
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?
Provides an explicit two-step workflow: first call with answers and consent=true to get a token, then call again with the same answers, consent, and token only if the person agrees. It also states exclusions ('NOT a purchase, NOT a guaranteed quote') and points to enquiry_fields for the answer keys.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
3 tool updates
- First observed
enquiry_describe - First observed
enquiry_fields - First observed
submit_enquiry
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TDQS
Each tool has a distinct role: enquiry_describe explains the process, enquiry_fields provides the schema, and submit_enquiry performs the submission. There is no overlap or ambiguity between them.
All names share the 'enquiry' theme and use snake_case, but the pattern is mixed: two are noun-first (enquiry_describe, enquiry_fields) while one is verb-first (submit_enquiry). This is readable but not a consistent verb_noun convention.
Three tools is well-scoped for a focused enquiry submission workflow. Each tool serves a necessary step with no redundancy.
The set covers the full flow: understanding what the enquiry is, retrieving the required fields, and submitting with confirmation. No essential operation appears to be missing for this narrow domain.