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Server Details
Metal Roof Cost Calculator: the site's own MCP server — calculator, enquiry (enquiry = a human...
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
5 toolscalculateMetal roof cost calculatorAInspect
Run the Metal roof cost calculator calculator: Actual roof area; Roofing squares (100 sq ft each); Panel area to order, including waste; Installed rate used, per sq ft. Missing inputs fall back to their documented defaults.
| Name | Required | Description | Default |
|---|---|---|---|
| rate | No | Your own installed price per sq ft (0 uses the panel default) | |
| panel | No | Panel type (sets a starting price per sq ft) | 14 |
| pitch | No | Roof pitch | 1.118 |
| waste | No | Waste allowance on material | |
| tearoff | No | Tear off the existing roof | 1 |
| footprint | No | Roof footprint (ground area under the roof) | |
| tearoffRate | No | Tear-off and disposal, per sq ft |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the behavioral burden; it discloses that missing inputs fall back to documented defaults and that the tool produces calculated quantities rather than performing an enquiry/submission. It does not explicitly state 'no side effects,' but a pure calculator's read-only nature is strongly implied by the output-oriented 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 one tight sentence with the action front-loaded and no filler beyond the redundant 'calculator calculator'. The semicolon-separated output list is compact and each item adds information. Minor word duplication prevents a 5.
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?
With no output schema, the description usefully enumerates four outputs (actual roof area, squares, panel area to order, installed rate used) and the default-fallback behavior. It is complete enough to invoke the tool with confidence, though it doesn't define the exact response structure or an explicit total-cost figure, which would be helpful for a 'cost calculator.'
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 already documents all 7 parameters with defaults and descriptions (100% coverage), which sets the baseline at 3. The description adds only the global fallback behavior and output names like 'Panel area to order, including waste' that slightly enrich waste semantics, but it does not compensate for or add much beyond the 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 names the exact action ('Run') and resource ('Metal roof cost calculator') and lists the computed outputs, so an agent can tell this is the calculation tool. It does not explicitly contrast it with calculator_describe or submit_enquiry, but the verb and output list are clear. The duplicated 'calculator calculator' is awkward but not confusing.
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 use case is implied by the title and the imperative 'Run'—this is the tool for computing metal-roof values, not for describing or enquiring. However, the description never states when to prefer it over the sibling tools or gives exclusions/prerequisites. The fallback-default note is an invocation rule, not usage routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculator_describeWhat Metal roof cost calculator computesAInspect
The inputs this calculator takes (with units, ranges and defaults), the outputs it returns, and the assumptions and tables behind it.
| 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, and it does disclose the core behavior: it returns a description of inputs, outputs, assumptions, and tables. It does not explicitly state that the tool itself performs no calculation or has no side effects, but the describe-oriented wording makes that largely apparent.
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 sentence that front-loads the key content: inputs, outputs, and assumptions/tables. Every phrase adds value and there is no redundancy.
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, no-output-schema descriptive tool, the description is fully sufficient. It names all the categories of information an agent would expect to receive, leaving no obvious gaps.
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 the baseline is 4 per the rubric. The description adds no parameter details for this call itself, but it does clarify that the tool describes the underlying calculator's parameters rather than accepting its own, which is enough.
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 precisely states that the tool conveys the calculator's inputs (with units, ranges, defaults), outputs, and underlying assumptions/tables. Combined with the name 'calculator_describe' and title, it is unambiguous and clearly distinct from the sibling's 'calculate'.
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 purpose implies this should be used when an agent needs to understand the calculator's inputs/outputs before calculating, and the sibling list includes 'calculate' as the natural alternative. However, there is no explicit statement of when to choose this over other tools or any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
enquiry_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 Metal Roof Cost Calculator: 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 burden, and it does well: it reveals that the tool returns who receives the details, the consent wording, and how the person confirms. It also clarifies key user-facing outcomes such as 'it is free' and 'no quote is guaranteed.'
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 and front-loaded with the most important usage signal ('Read first'). Every sentence earns its place: what the tool does, what it does not do, and what it returns.
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 zero parameters, no output schema, and no annotations, the description provides enough context for an agent to know exactly why this tool exists, when to read it, and what information it will return. Nothing essential is missing for a describe-style tool.
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 there is no parameter burden for the description to carry. The schema already fully covers the empty parameter set, and the description adds no unnecessary parameter-related content.
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 verb-resource pair: it 'states plainly what submit_enquiry does' on the Metal Roof Cost Calculator. It also clearly differentiates itself from the actual submission action by clarifying that nothing is bought, ordered, or paid and no quote is guaranteed.
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' gives a clear directive to consult this tool before taking action, and the description explains what kind of information the agent will gain. It does not explicitly name when to prefer sibling tools, but the 'not a purchase, not a guaranteed quote' framing implicitly tells the agent this is informational rather than transactional.
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 Metal Roof Cost Calculator 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 available, the description carries the burden of behavioral disclosure. It successfully describes what the tool returns (field metadata) and implies a read-only, non-mutating behavior by directing mutation to submit_enquiry. It does not mention errors or edge cases, but for a simple field-listing 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?
A single sentence packs the resource, the exact output contents, and a downstream usage instruction with no filler. The most important information is front-loaded, and every clause 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?
The description is complete enough for a simple metadata-retrieval tool with no parameters and no output schema. It covers what fields are returned and how to use them, and despite not mentioning sibling tools like enquiry_describe, the field-focused scope is clear.
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 adds useful contextual information by explaining that returned field keys are meant to be used as keys for submit_enquiry, which helps an agent understand how the no-input tool fits into the larger workflow.
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 as 'Every field of the Metal Roof Cost Calculator enquiry' and enumerates the exact content: key, label, type, required status, help text, and allowed options. It implies a retrieval/description purpose and distinguishes itself from submit_enquiry, though it lacks an explicit verb like 'get' or 'list'.
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 clear usage context by stating 'Pass answers to submit_enquiry keyed by field key,' which tells an agent how to use the field keys after fetching them. It does not explicitly contrast against enquiry_describe or calculator_describe, but the intended workflow is clear.
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 Metal Roof Cost Calculator — 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 a local metal roofing contractor, who'll contact 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 a local metal roofing contractor, who'll contact 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?
No annotations are present, so the description carries the full burden, and it delivers: it discloses the two-step flow, that no purchase/quote is guaranteed, that consent text must be shown, that an email with a link is sent, and that providers only see the enquiry after the link is clicked. This is unusually complete 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 front-loads the core purpose and disambiguation before a clearly separated Step 1/Step 2 breakdown. All included details—consent line, email link, token—are necessary for correct invocation, and nothing extraneous remains.
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 or annotations, the description covers preconditions, step outputs, and post-conditions (email, provider visibility after click). Minor gaps remain around failure modes and what step 2 returns, but the agent has enough to execute the flow correctly.
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 already describes each parameter with 100% coverage, and the description adds key meaning: answers are keyed by field key from enquiry_fields, consent must literally be true with quoted consent text, and confirmation is the token returned in step 1. This enriches the schema without being redundant.
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 the exact verb 'Submits an enquiry', names the resource 'Metal Roof Cost Calculator', and immediately disambiguates from purchase/quote. The two-step process and consent requirement make the tool's role unmistakable even among 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?
Provides a precise two-step workflow (first call with answers+consent, second call with confirmation token after approval) that tells an agent exactly when and how to invoke it. It does not explicitly compare against sibling tools such as calculate or enquiry_fields, though the procedural guidance makes the intended context clear.
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.
5 tool updates
- First observed
calculate - First observed
calculator_describe - First observed
enquiry_describe - First observed
enquiry_fields - First observed
submit_enquiry
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TDQS
Each tool serves a distinct purpose: calculate runs the calculator, calculator_describe explains it, enquiry_describe explains the enquiry flow, enquiry_fields lists inputs, and submit_enquiry performs the submission. There is no overlap or ambiguity between them.
Tool names mix styles: calculate and submit_enquiry use verb_noun, while calculator_describe and enquiry_describe use noun_verb, and enquiry_fields is noun_noun. The pattern is inconsistent and does not follow a single predictable convention, though the names are still descriptive.
With 5 tools covering two clear functions (calculator and enquiry), the count is well-scoped. Each tool earns its place without redundancy or unnecessary bloat.
The surface fully covers the domain: calculation with execution and description, and enquiry with explanation, field listing, and a two-step submission flow. There are no missing operations or dead ends for the stated purpose.