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Server Details
Drain Prices: the site's own MCP server — enquiry (enquiry = a human handoff, not a purchase);...
- Status
- Healthy
- Uptime
- 99.7% over 38 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
Scored across 3 tools
The three tools have distinct roles: enquiry_describe explains behavior, enquiry_fields returns the schema, and submit_enquiry performs the submission. The two-step confirmation flow lives inside submit_enquiry, so there is no real overlap, though describe/fields are closely related and could momentarily blur.
Two tools use an enquiry_ prefix (enquiry_describe, enquiry_fields) while the third uses submit_enquiry, mixing noun-first and verb-first conventions. It is readable and the domain noun is shared, but the pattern is not predictable.
Three tools is a reasonable, tightly scoped set for a single-purpose enquiry submission server. It is on the lean side but each tool clearly earns its place in the describe-fields-submit workflow.
The narrow domain (collecting and submitting an enquiry) is fully covered: behavior description, field schema, and a validated two-step submission with consent. Minor gaps like enquiry status or cancellation are arguably out of scope.
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 Drain 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, the description carries full burden. It discloses the tool's behavior: it returns who receives details, consent wording, and confirmation method. It implies read-only behavior through 'Read first' and the focus on explanation, but does not explicitly state side effects or limitations. Since it's a description tool, this is sufficient.
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, starting with the imperative 'Read first,' which front-loads the usage instruction. The second sentence elaborates concisely on what the tool returns. It's appropriately sized for a simple describe tool, though it could be tightened.
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 and no output schema, the description provides all essential information: what the tool does and what it returns. It covers the key aspects of submit_enquiry that an agent needs to understand before using it. There are no gaps that would prevent correct invocation.
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 the baseline is 4. The description doesn't need to explain parameters, and it doesn't. The schema coverage is 100% (empty schema), so no information is missing.
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: to describe what submit_enquiry does, with specific details about its behavior (no purchase, no guaranteed quote, free). It distinguishes itself from submit_enquiry (which performs the action) and implies a different role from enquiry_fields by focusing on explanation 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 'Read first' explicitly instructs to use this before submit_enquiry. It doesn't mention alternatives or exclusions, but the context of 'what submit_enquiry does' makes it clear this is for understanding, not for performing the enquiry. It could be improved by explicitly stating when to use it instead of the other tools, but the guidance is adequate.
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 Drain 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 and no output schema, the description carries the behavioral transparency burden, and it does disclose the exact contents of the returned field information: key, label, type, required flag, help text, and allowed options. It could be more explicit about being read-only, but the nature of a field-listing tool makes that reasonably inferable.
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 exactly what the tool provides, and the second connects the output to the sibling submission tool. 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?
Given that the tool has no parameters, no annotations, and no output schema, the description conveys enough to use it: what the fields are and how their keys connect to submit_enquiry. It would be marginally more complete if it explicitly distinguished this tool from enquiry_describe.
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 coverage is 100%, so the description does not need to explain parameter semantics. This matches the baseline of 4 for a no-parameter tool.
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 identifies the resource ('Every field of the Drain Prices enquiry') and enumerates the exact attributes exposed, which makes the tool's purpose clear. However, it lacks an explicit verb like 'returns' or 'lists', so it is slightly weaker than a fully direct purpose statement.
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 provides clear usage context by telling the agent to pass answers to submit_enquiry keyed by field key, which signals that this tool should be used to discover the enquiry schema before submission. It does not explicitly contrast with enquiry_describe, so it stops short of full alternative-routing guidance.
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 Drain 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: "Send my contact details to up to three relevant local drainage engineers, chosen by Drain Prices, 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 relevant local drainage engineers, chosen by Drain Prices, 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: it discloses that step 1 validates and returns a summary, consent line and token, that step 2 actually submits and triggers an email, and that the recipient must click a link before any provider sees the enquiry. It also spells out the downstream consequence (contact details go to up to three chosen engineers who contact the person directly, with the ability to stop further firms).
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 purpose and the two negations, then the two steps in order, so the critical routing information comes first. The embedded verbatim consent paragraph is long and is duplicated in the schema's consent field description, which is mild redundancy, though arguably required for legal precision.
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 output schema and no annotations, the description covers everything an agent needs: the two-step protocol, the token handoff, what each call returns, the consent condition, and the downstream email-confirmation gate before providers see the data. Nothing material 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 description coverage is 100%, so baseline is 3, but the description adds real meaning beyond it: 'answers' is keyed by field key sourced from the sibling enquiry_fields tool, and the confirmation token is explicitly tied to step 1 and to prior human approval. It also reinforces that the same answers must be resubmitted in step 2, a sequencing constraint the schema does not express.
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 Drain Prices') and immediately delimits it from what an agent might assume ('NOT a purchase, NOT a guaranteed quote'). The two-step framing distinguishes it cleanly from the sibling enquiry_fields and enquiry_describe tools, which are clearly preparation steps.
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 conditional flow: Step 1 with answers + consent=true, show the summary and consent line, then Step 2 only if the person agrees, passing the confirmation token. It also states the pre-condition for consent (the person has read and agreed to the quoted text), so an agent knows exactly when each call is legal.
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 relevant local drainage engineers, who'll price the job directly."New value: +"true only when the person has agreed to: Send my contact details to up to three relevant local drainage engineers, chosen by Drain Prices, 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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