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Server Details
Leave Loading Calculator: the site's own MCP server — calculator, enquiry (enquiry = a human...
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
5 toolscalculateAnnual leave loading calculatorBInspect
Run the Annual leave loading calculator calculator: Base weekly pay; Base pay for the leave period; Leave loading; Penalties you would have earned. Missing inputs fall back to their documented defaults.
| Name | Required | Description | Default |
|---|---|---|---|
| hourlyRate | No | Base hourly rate | |
| leaveWeeks | No | Weeks of annual leave being paid | |
| loadingPct | No | Leave loading in your award or agreement | |
| penaltyPct | No | Weekend or shift penalties you normally get | |
| hoursPerWeek | No | Ordinary hours per week |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It does disclose that missing inputs fall back to documented defaults and lists the computed outputs, but it does not explain how results are returned, what assumptions or formulas are used, or whether the tool is a pure computation with no side effects.
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 with no wasted words beyond the duplicated 'calculator' typo. The key outputs are front-loaded and the default behavior is mentioned, making it efficient despite minor grammatical awkwardness.
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 calculator with all-optional parameters that are fully documented in the schema, the description covers the outputs and default behavior. However, since there is no output schema and no annotations, the response shape and the relationship between inputs and outputs are left unstated, requiring inference.
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%, with all five parameters having names, descriptions, defaults, and ranges. The description adds only generic default-fallback context, which aligns with the schema, so it does not need to repeat individual parameter semantics.
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 says to run the annual leave loading calculator and enumerates the outputs: base weekly pay, base pay for the leave period, leave loading, and penalties. This makes the operation and resource clear, though the wording is awkward ('calculator calculator') and it does not explicitly differentiate itself from siblings like calculator_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?
There is no guidance on when to use this tool versus alternatives such as calculator_describe or submit_enquiry. The only usage-related information is about default fallback, which is behavioral rather than selection guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculator_describeWhat Annual leave loading 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 of behavior. It discloses the content scope (inputs, outputs, assumptions, tables), which is useful, but it does not clarify that the tool itself is read-only, how results are returned, or that it does not perform calculations.
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 with no filler. It packs the key content categories into a compact, front-loaded description.
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, the description covers the essential content categories an agent needs to know. It could be stronger by explicitly saying it returns a description and not a calculation, but the name and sibling context mitigate this.
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 an empty input schema, so there are no useful parameter details to add. The description appropriately references the calculator's inputs rather than the tool's own parameters, which is coherent for a describe-style 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 clearly identifies the tool as providing the calculator's inputs (with units, ranges, defaults), outputs, assumptions, and tables. It is specific and informative, though it does not explicitly name or contrast the sibling calculate tool.
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?
No explicit guidance is given for when to use this tool versus calculate or enquiry_describe. The description implies it is informational, but it does not state exclusions or alternatives.
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 Leave Loading 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 provided, the description carries the behavioral disclosure burden. It transparently explains that the described action is free, involves no purchase or payment, and does not guarantee a quote. It also discloses the return contents: recipient details, consent wording, and confirmation method. It does not explicitly mention whether this tool itself is read-only, but its descriptive nature and 'returns' phrasing imply it.
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-loads the most important instruction with 'Read first'. Each sentence conveys useful information without repetition, though the title is somewhat long and the phrasing occasionally reads more like user-facing copy than a tool definition.
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 descriptive tool, the description is sufficiently complete: it explains what the tool covers, what the underlying action entails, and what information will be returned. With no output schema, mentioning the return contents specifically helps an agent know what to expect.
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 for the description to explain. The baseline for a zero-parameter tool is 4, and the description correctly makes no parameter claims that could conflict with 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 clearly states that the tool explains what submit_enquiry does on the Leave Loading Calculator, using the verb 'states' with a named resource. It also says the tool returns who receives the details, the consent wording, and how the person confirms. However, it does not explicitly differentiate itself from sibling tools like calculator_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 opening 'Read first' gives clear contextual guidance to consult this description before using submit_enquiry. The description also clarifies what the underlying action does and does not do, such as 'Nothing is bought, ordered or paid' and 'no quote is guaranteed'. It stops short of naming alternatives or explicitly stating when not to use this 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 Leave Loading 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 provided, the description carries the full burden of behavioral disclosure. It describes the output content but does not explicitly state that the operation is read-only or free of side effects. While the nature of the tool implies a safe read, this is not stated, leaving some ambiguity.
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, dense sentence that front-loads the key information (what fields are returned) and then provides a practical usage hint. No wasted words.
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 covers what it returns and how to use it. It could specify the return format (e.g., an array) but the list of attributes sufficiently informs the agent. Overall, it is adequate.
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. The description does not need to explain parameters, and it correctly focuses on the output. No additional parameter semantics are 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 states a specific resource (the Leave Loading Calculator enquiry fields) and lists the attributes returned (key, label, type, required, help text, options). This is clear and distinct from a general enquiry description, though it does not explicitly name a sibling tool for differentiation.
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?
It provides direct usage guidance: 'Pass answers to submit_enquiry keyed by field key.' This tells the agent how to apply the returned fields and implies calling this tool before submitting. It does not explicitly contrast with alternatives, but the context 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 Leave Loading 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 workplace relations adviser or payroll specialist, 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 workplace relations adviser or payroll specialist, 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?
With no annotations provided, the description carries full burden. It discloses the two-step nature, the non-purchase/non-quote status, the consent requirement (including the exact consent text), and that an email link must be clicked before any provider sees the enquiry. This is highly transparent about side effects and prerequisites.
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?
Although lengthy, every sentence serves a purpose. The description is front-loaded with the key distinction (NOT a purchase), then flows logically through step 1 and step 2, including the exact consent text. No redundancy or filler.
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 two-step tool with consent and confirmation token, the description covers the entire workflow: validation, summary display, consent line, token reuse, final submission, and email link requirement. Without an output schema, it explains what to show the user (summary and consent line). No critical information 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 schema documents each parameter. The description adds meaningful context: it explains that 'confirmation' is the token from step 1, that 'answers' must be the same in both calls, and that 'consent' must be true. This goes beyond the schema's basic descriptions.
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 explicitly states the tool submits an enquiry, and immediately clarifies it is NOT a purchase or guaranteed quote. It distinguishes from siblings by naming the two-step flow and the consent requirement, leaving no ambiguity about what the tool does.
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 explicit step-by-step usage: step 1 for validation with answers and consent, showing the summary, then step 2 only if the person agrees, using the same answers plus the confirmation token. It also specifies the condition for proceeding (person agrees) and the email click requirement, which is essential for correct usage.
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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/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
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TDQS
Each tool targets a distinct function: calculating, describing the calculator, describing the enquiry flow, listing enquiry fields, and submitting the enquiry. Even the two 'describe' tools are clearly separated by subject matter (calculator vs. enquiry).
Naming patterns are inconsistent: 'calculate' is a bare verb, 'submit_enquiry' is verb_noun, while 'calculator_describe' and 'enquiry_describe' are noun_verb, and 'enquiry_fields' is noun_noun. The mixed conventions make the toolset feel less predictable.
Five tools is well-scoped for a calculator-plus-enquiry site. Each tool has a clear role and none feel redundant or missing.
The surface covers the full user journey: describe the calculator, run the calculation, understand the enquiry, get the field schema, and submit with consent confirmation. No obvious dead ends or missing operations for this domain.