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Server Details
TM44 Quote: the site's own MCP server — enquiry (enquiry = a human handoff, not a purchase);...
- 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 TM44 Quote: 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, the description carries the burden of explaining behavior. It says the tool 'States plainly' what another tool does and 'Also returns' the recipients, consent wording, and confirmation method, making clear it is an informational/return-value-producing tool. It stops short of explicitly stating 'this tool has no side effects,' but for a description-oriented zero-parameter tool the transparency is adequate.
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 short, front-loaded with 'Read first', and covers purpose, key content, and return information in three sentences. It is slightly repetitive with the title ('not a purchase, not a guaranteed quote'), but it remains efficient and well structured.
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 tool with no parameters, no output schema, and no annotations, the description gives enough context to understand what the tool returns and why it should be called first. It names the related submit_enquiry process and key output aspects, though it does not navigate the sibling tool relationship with enquiry_fields.
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 zero properties, so the baseline is 4. The description adds no parameter information because there are no parameters to document. This is appropriate and needs no further compensation.
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 'States plainly what submit_enquiry does' and describes the result as an explanation rather than an action. It names the relevant resource and context (TM44 Quote) and the title reinforces that this is informational, not a purchase or guaranteed quote. It does not explicitly distinguish itself from enquiry_fields, so it is not quite 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?
'Read first' is an explicit usage cue that positions this tool as the prerequisite before using submit_enquiry. It makes the context clear: use this to understand what happens when an enquiry is submitted. It does not mention alternatives such as enquiry_fields or state when not to use this tool, so it falls short of full guidance.
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 TM44 Quote 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 behavioral disclosure burden. It states exactly what information the tool exposes and that it covers every field. It does not describe the return format or explicitly state that it is read-only, but for a simple metadata-fetching tool the core behavior is clear enough.
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 compact: one sentence enumerates the returned field attributes, and a second sentence connects the result to submit_enquiry. Every sentence earns its place and the most important information is front-loaded.
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 metadata tool, the description covers the output contents and the expected downstream usage well. The main gaps are the lack of explicit contrast with enquiry_describe and no mention of the exact output shape, but these are minor given the tool's simplicity.
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 zero parameters, so there are no parameter semantics to document. The baseline for zero-parameter tools is 4, and the description adds useful context by explaining how the returned field keys connect to submit_enquiry.
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 identifies the tool as returning every field of the TM44 Quote enquiry, including key, label, type, required status, help text, and options. It distinguishes itself from submit_enquiry by stating that answers should be keyed by field key, though it lacks an explicit verb such as 'list' or 'return' and does not differentiate from enquiry_describe.
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 a concrete usage direction: pass answers to submit_enquiry keyed by field key. This tells the agent how the output should be used with the submission sibling. However, it does not explicitly state when to use this tool over enquiry_describe or provide exclusion criteria.
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 TM44 Quote — 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 accredited air conditioning energy assessors, 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 accredited air conditioning energy assessors, 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 provided, the description carries the full burden—and it delivers: it explains the two-step stateful behavior, the consent requirement, the email confirmation step, and that providers only see the enquiry after the person clicks the link. It also discloses that this is not a guaranteed quote, which sets accurate expectations about outcomes.
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 rich but compact: it front-loads the critical 'not a purchase' caveat, then structures the workflow as Step 1 and Step 2. Every sentence earns its place, including the exact consent wording the agent must 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 complex, stateful mutation tool with no annotations and no output schema, the description is remarkably complete. It covers the full call sequence, what each call returns, the required consent text, the email-link behavior, and the post-consent approval step—so an agent knows what to do and what will happen.
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?
Although the schema already documents all parameters at 100% coverage, the description adds essential meaning: answers must be keyed by field keys from enquiry_fields, consent must match the exact consent line, and confirmation is the token returned from step 1. This clarifies how the parameters relate to each other across the two-step flow.
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 TM44 Quote', and immediately clarifies what it is NOT ('NOT a purchase, NOT a guaranteed quote'). This separates it clearly from the sibling tools enquiry_describe and enquiry_fields, as those describe or list fields rather than submit anything.
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 a clear two-step usage protocol: first call for validation and a token, then a second call only after the person agrees. It points to enquiry_fields as the source of answer keys, but it does not explicitly say when to prefer this tool over enquiry_describe or when the tool should not be used beyond 'not a purchase.'
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: one explains the workflow, one provides the field schema, and one submits the enquiry. There is no meaningful overlap or ambiguity between them.
Two tools use the 'enquiry_' prefix pattern, while the third inverts the order to 'submit_enquiry'. The names are still readable and understandable, but the verb/noun ordering is not fully consistent.
Three tools are well-scoped for a single, focused submission workflow. Each tool serves a necessary purpose and the set does not feel bloated or incomplete for its stated scope.
The server covers the full enquiry submission lifecycle: describing the process, enumerating required fields, validating, confirming consent, and submitting. There are no obvious dead ends within the stated purpose.