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Server Details
Industrial Flooring Cost: the site's own MCP server — enquiry (enquiry = a human handoff, not a...
- Status
- Healthy
- Uptime
- 99.9% over 43 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
Scored across 3 tools
Each tool has a clearly distinct role: enquiry_describe explains the process, enquiry_fields returns the schema, and submit_enquiry performs the two-step submission. There is no overlap in purpose or target, so an agent cannot confuse them.
All three names use snake_case and share the 'enquiry' domain token, which makes the set readable and grouped. There is a minor deviation in verb placement (enquiry_describe/enquiry_fields are noun-first while submit_enquiry is verb-first), but the convention is otherwise stable.
Three tools is well matched to a narrow, single-purpose lead-capture flow: one to explain, one to enumerate fields, one to submit. Each tool earns its place and nothing is redundant or missing from the count perspective.
The surface covers the full enquiry lifecycle the tools advertise: explanation, field discovery, and validated two-step submission with consent. The only gap is the absence of any operation to inspect, amend, or withdraw a submitted enquiry, which agents can largely work around since provider contact is stopped via email.
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 Industrial Flooring Cost: 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 at all, the description carries the full burden, and it excels: it discloses that no purchase, order, or payment occurs, that quotes are not guaranteed, that the service is free, and that the tool returns who receives details, consent wording, and confirmation behavior. This is unusually thorough behavioral disclosure.
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, front-loaded with 'Read first', and every sentence earns its place. It efficiently covers the tool's informational purpose, key disclaimers, and what it returns without unnecessary elaboration.
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 informational tool with no output schema, the description fully equips an agent to decide when to call it and what to expect. It covers the core behavior, exceptions, and return details, leaving no critical 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 tool has zero parameters and the schema already covers this completely, so no parameter documentation is needed. Per the zero-parameter baseline, a 4 is appropriate since the description adds no parameter detail but none is required.
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 this tool explains what submit_enquiry does, using an explicit verb ('states plainly') and specific resource context ('Industrial Flooring Cost'). It distinguishes itself from submit_enquiry by describing rather than performing the enquiry action, and from enquiry_fields by focusing on behavioral outcomes rather than fields.
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 opening phrase 'Read first' gives an explicit usage directive, implying this should be consulted before calling submit_enquiry. It does not explicitly discuss when to use enquiry_fields or when not to use this tool, but the context strongly suggests it is the preliminary informational tool.
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 Industrial Flooring Cost 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 provided, the description carries the burden of behavioral disclosure. It does this well by stating exactly what data the tool exposes and noting that options are included only 'where there are any'. It does not describe response structure or potential edge cases, but the tool is a simple zero-parameter read operation.
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?
Two sentences with no filler. The first sentence states the tool's scope and content, and the second connects it directly to the downstream submit_enquiry workflow. Every sentence earns its place.
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, zero-parameter, no-output-schema introspection tool, the description is nearly complete: it describes the returned field metadata and how to use it. The only notable gap is the lack of any mention of the sibling enquiry_describe, which could leave an agent unsure which tool to pick in a broader workflow.
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 no parameters and the input schema is empty, so there is nothing to document. The description adds meaningful semantic context by explaining that the returned field keys are the ones to use when submitting answers to submit_enquiry, which is helpful despite there being no parameters.
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 resource: every field of the Industrial Flooring Cost enquiry, and lists exactly what is returned (key, label, type, required, help text, options). It does not use an explicit verb like 'returns' or 'lists', and it does not distinguish itself from the sibling enquiry_describe, so it falls just 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 phrase 'Pass answers to submit_enquiry keyed by field key' implies that this tool should be used to discover valid keys before calling submit_enquiry. However, there is no explicit when-to-use/when-not-to-use guidance and no differentiation from enquiry_describe, so usage context is only implied.
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 Industrial Flooring Cost — 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: "Send my contact details to up to three local industrial flooring contractors, chosen by Industrial Flooring Cost, who'll contact me directly. I'll be emailed each firm's name as my details go to it, and can stop any more firms getting them."
| Name | Required | Description | Default |
|---|---|---|---|
| answers | Yes | the person's answers, keyed by field key | |
| consent | Yes | true only when the person has agreed to: Send my contact details to up to three local industrial flooring contractors, chosen by Industrial Flooring Cost, who'll contact me directly. I'll be emailed each firm's name as my details go to it, and can stop any more firms getting them. | |
| 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, the description carries the full behavioral burden and does so: it discloses the two-phase submit/confirm design, what step 1 returns (summary, consent line, token), that the enquiry is not visible to providers until an emailed link is clicked, and the exact downstream scope (up to three contractors, name disclosed as details are shared, opt-out possible). This is precisely the context annotations could never encode.
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?
Front-loaded with the key distinction ('NOT a purchase'), then structured as Step 1 / Step 2. The embedded consent quotation is long and repeats the schema's consent description, but it is legally load-bearing text that the agent must surface verbatim, so it earns its place.
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 nested-parameter tool with no output schema and no annotations, the description supplies everything needed: the two-call flow, the token round-trip, the meaning of consent, the return contents of step 1, and the post-submission verification gate. It also routes the agent to enquiry_fields for the answer keys, so no prerequisite is missing.
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?
Schema coverage is 100%, so the baseline is 3, but the description adds real meaning: the answers object is keyed by the field key drawn from enquiry_fields, consent must be true, and the confirmation token is the step-1 token used only after the person approves the summary. That clarifies parameter provenance and sequencing beyond the schema text.
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 ('submits an enquiry') and resource, and immediately scopes it with 'NOT a purchase, NOT a guaranteed quote' — a distinction that matters for an agent deciding whether to invoke. It also references the sibling tool enquiry_fields as the source of field keys, so the tool is distinguishable from its siblings without opening a schema.
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?
Gives an explicit two-step protocol: step 1 with answers+consent to get a token and show the summary, step 2 only if the person agrees, with the token added. It states the precondition for step 2 ('only if the person agrees') and what must be shown to the person, leaving no inference about ordering or gating.
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.
1 tool update
- Changed
submit_enquiry1 field changed- changed
Input schema / properties / consent / descriptionPrevious value: -"true only when the person has agreed to: Happy for my details to go to local industrial flooring contractors, who'll quote me directly."New value: +"true only when the person has agreed to: Send my contact details to up to three local industrial flooring contractors, chosen by Industrial Flooring Cost, who'll contact me directly. I'll be emailed each firm's name as my details go to it, and can stop any more firms getting them."
3 tool updates
- First observed
enquiry_describe - First observed
enquiry_fields - First observed
submit_enquiry
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