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Server Details
Fire Alarm Servicing Cost: 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 Fire Alarm Servicing 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, the description carries the behavioral disclosure burden and does well: it states the action is free, involves no purchase/order/payment, provides no guaranteed quote, and returns recipient/consent/confirmation details. It does not explicitly declare the tool itself as read-only, but the informational nature is strongly implied.
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 at three sentences and front-loads the 'Read first' instruction. Minor redundancy exists between the title ('not a purchase, not a guaranteed quote') and the description ('Nothing is bought, ordered or paid; no quote is guaranteed'), but each 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 zero-parameter, informational tool with no output schema, the description covers what the tool returns and what assumptions to avoid. It lacks an explicit statement of output format, but that is a minor gap given the low complexity and explanatory purpose.
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 is empty with zero parameters, so there are no parameter semantics to explain. The description adds useful context about what is returned, but no parameter-level documentation is needed; baseline 4 applies.
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 an explanatory preamble to submit_enquiry: 'States plainly what submit_enquiry does' and clarifies what is not happening ('Nothing is bought, ordered or paid'). It distinguishes the describe action from the actual submission action, though it does not explicitly frame itself as 'describes the enquiry flow' beyond that.
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' gives a clear ordering cue to use this before submit_enquiry, and the title warns it is not a purchase or guaranteed quote. However, it does not mention the sibling enquiry_fields or explain when to prefer this tool over that alternative, so usage guidance is partial rather than complete.
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 Fire Alarm Servicing 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?
No annotations are present, so the description carries the behavioral disclosure burden. It clarifies that the tool is a metadata lookup by describing the fields and by implying that submission happens through 'submit_enquiry', meaning this tool itself does not submit. It does not discuss permissions, rate limits, or response shape, but these are less critical for a zero-parameter read-only introspection tool.
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 carry the content and downstream usage with no filler. The description front-loads the resource and field-info list before the usage note, making it easy to scan.
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 no-parameter lookup with no output schema, the description sufficiently specifies the returned information and how it should be used. It might be clearer with an explicit output shape or a note distinguishing it from 'enquiry_describe', but nothing critical 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?
The tool has zero parameters, so the schema trivially covers 100% of parameters. With no parameters to document, the baseline is 4; the description's mention of 'key' and 'allowed options' helps contextualize the data consumers will need, but nothing more 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 identifies the specific resource ('Fire Alarm Servicing Cost enquiry') and enumerates the field metadata ('key, label, type, whether required, help text...'), making the tool's purpose clear. However, it uses the noun phrase 'Every field of...' rather than an explicit verb like 'returns' or 'lists', and it does not directly distinguish the tool from the sibling '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 second sentence gives actionable guidance: 'Pass answers to submit_enquiry keyed by field key,' which tells the agent to use this tool to discover field keys before submitting. It does not mention 'enquiry_describe' or state when not to use the tool, so it lacks explicit exclusions.
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 Fire Alarm Servicing 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: "Happy for my details to go to relevant fire alarm servicing companies, 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 fire alarm servicing companies, 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 does so thoroughly: it discloses validation, the summary/consent line/token returned in step 1, the need for a second call, and the email-link click requirement before providers see the enquiry. It also spells out the exact consent wording, leaving no hidden behavior.
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 longer than average, but every sentence earns its place given the two-step, consent-sensitive workflow. It is front-loaded with the most important caveat (not a purchase/quote) and then logically structured around steps 1 and 2.
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 multi-step tool with no output schema and no annotations, the description is remarkably complete: it explains what to send, what comes back in step 1, when to make the second call, the consent requirement, the email-link step, and the practical consequence for the user. Nothing essential 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?
Although schema coverage is already 100%, the description adds meaningful semantics: answers are keyed by field key from enquiry_fields, consent must be true and match the quoted wording, and confirmation must be the token from step 1 after approval. This goes well beyond the raw schema.
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 states a specific action ('Submits an enquiry'), identifies the target resource (Fire Alarm Servicing Cost / human providers), and explicitly distinguishes itself from a purchase or guaranteed quote. It also frames the two-step submission flow clearly, making its role distinct from sibling tools like enquiry_describe and enquiry_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 description gives explicit step-by-step invocation guidance: call first with answers and consent=true, show the summary, then call again with the confirmation token only if the person agrees. It also states what the tool is NOT for (not a purchase, not a guaranteed quote), giving clear when-not-to-use context.
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 clearly distinct role: one explains the process, one provides the field schema, and one submits the enquiry. There is no overlap between them, so an agent can confidently select the right tool for each step.
The names are readable and semantically related, but the patterns are mixed: enquiry_describe and enquiry_fields lead with the noun, while submit_enquiry follows verb_noun. This is a minor inconsistency rather than chaos, so it earns a middle score.
Three tools is well-scoped for a narrowly defined enquiry submission workflow. Each tool earns its place: orientation, schema discovery, and submission.
The tool surface fully covers the enquiry lifecycle described: explaining the process, enumerating required fields, and submitting with explicit consent and confirmation handling. No obvious missing step or dead end exists for the stated purpose.