Server Details
Contractor Pay Calculator: the site's own MCP server — calculator, enquiry (enquiry = a human...
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
5 toolscalculateDay rate take-home calculatorBInspect
Run the Day rate take-home calculator calculator: Annual invoice value; Umbrella margin (£25/week); Gross pay (after employer costs); Employer NI (15%, funded from your rate). Missing inputs fall back to their documented defaults.
| Name | Required | Description | Default |
|---|---|---|---|
| ir35 | No | IR35 status | inside |
| dayRate | No | Day rate | |
| expenses | No | Annual business expenses (outside IR35 only) | |
| daysPerWeek | No | Days worked per week | |
| weeksPerYear | No | Working weeks per year |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It meaningfully reveals assumptions: umbrella margin is £25/week, Employer NI is 15% funded from the rate, and gross pay is after employer costs. It also states that missing inputs use documented defaults. It doesn't describe the output format, but for a pure calculator this is acceptable transparency.
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 only one sentence, so it is concise, but it contains the awkward repetition 'calculator calculator' and a semicolon-separated list that is not explicitly labeled as inputs, outputs, or assumptions. It is front-loaded with the main action, but the structure is slightly muddled.
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 tool has five optional parameters, no output schema, and no annotations, so the description should clarify what the result is. It lists several calculation components, which partially answers this, but it never explicitly states that the tool returns an estimated take-home amount or how IR35 status affects the calculation. This is a meaningful 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?
Schema description coverage is 100%, so the schema already documents each parameter and its default. The description adds a general fallback-to-defaults note and calculation assumptions, but it does not enrich individual parameter meanings beyond what the schema provides. Baseline 3 is appropriate.
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 uses the verb 'Run' and clearly identifies the resource as the 'Day rate take-home calculator', so an agent can tell this is a calculation tool. The list of components (Annual invoice value, Umbrella margin, Gross pay, Employer NI) hints at what the tool computes, though it does not explicitly state 'take-home pay'. The redundant 'calculator calculator' phrasing slightly weakens an otherwise clear purpose.
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 about when to use this tool versus alternatives like calculator_describe or submit_enquiry. The only usage-related note is that missing inputs fall back to defaults, which is about behavior rather than tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculator_describeWhat Day rate take-home 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?
No annotations exist, so the description must carry behavioral/safety information. It discloses the content returned (inputs, outputs, assumptions, tables), which implies a read-only informational call. It does not explicitly state side-effect-free behavior or the output format, but for a describe tool this is adequate.
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?
One tight sentence that front-loads all key content areas. No filler or repetition of the schema.
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 and no output schema, the description names the return dimensions (inputs, outputs, assumptions, tables) sufficiently for an agent to judge relevance. It could explicitly note that no calculation is performed and that the result is informational, but sibling naming makes this inferable.
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 carries no semantics; baseline is 4. The description compensates by specifying that the tool will describe parameter units, ranges, and defaults for the calculator, adding conceptual meaning beyond the empty 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 identifies a documentation/describe purpose: it will relay the calculator's inputs (with units, ranges, and defaults), outputs, and underlying assumptions and tables. The title reinforces this. It does not explicitly contrast with sibling `calculate`, but the describe-vs-calculate distinction is evident.
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 implies the tool is the reference for understanding the calculator, so an agent would call it before or instead of `calculate` when needing semantics. However, it never states when to prefer this over siblings or gives exclusions, leaving the decision to inference.
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 Contractor Pay 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 to carry the safety profile, the description fully discloses the tool's behavior: nothing is bought, ordered, or paid; no quote is guaranteed; it is free; and it returns who receives the details, the consent wording, and how the person confirms. This goes well beyond what the empty schema or title alone could convey.
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?
Three short sentences are front-loaded with the most important instruction ('Read first') and then state the core behavior, the non-purchase guarantee, and the returned information. Every clause earns its place without jargon or padding.
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 describe tool, the description is self-sufficient: it clarifies what this tool is for, what it is not (a purchase/quote), and what information it returns. An agent can decide to call it before submit_enquiry without any missing context.
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 and 100% coverage by definition, so there is nothing for the description to clarify. The baseline of 4 for parameterless tools applies, and the description appropriately focuses on behavior and return content instead of inputs.
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 a specific verb ('states plainly'), the subject ('what submit_enquiry does on Contractor Pay Calculator'), and the scope (an enquiry with human providers who quote directly). It clearly separates this descriptive tool from the actual submit_enquiry sibling by framing itself as a read-first explanation rather than the action.
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' is an explicit placement cue telling the agent to consult this tool before using submit_enquiry, and the description makes it obvious this is the explanatory counterpart to that action. It doesn't explicitly rule out alternatives such as enquiry_fields or calculator_describe, but the context is clear enough for a zero-parameter description 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 Contractor Pay 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, the description carries the burden of behavioral disclosure. It explains what content is returned but does not state the return format (array vs object), whether authentication is required, or that the operation is read-only. Given the tool's simple informational nature, these gaps are acceptable but leave some uncertainty.
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 compact sentences, front-loaded with the core content and followed by a practical usage pointer. Every sentence earns its place; no filler or repetition.
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 no-parameter metadata tool, the description is nearly complete: it lists the field attributes, mentions allowed options, and connects to submit_enquiry. The absence of an output schema is partially mitigated by listing the returned attributes, though it stops short of describing whether results are a list or keyed object.
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 accepts zero parameters, and the schema coverage is 100% (vacuously), so the baseline is 4. The description adds no parameter details because there are none, but it usefully explains that output field keys are meant to be used as keys in submit_enquiry, which clarifies the relationship without describing parameters of this 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 resource (fields of the Contractor Pay Calculator enquiry) and the data exposed (key, label, type, required, help text, allowed options). It lacks an explicit verb like 'lists' or 'returns', but the colon structure and content make the purpose clear. It is distinguishable from sibling tools such as submit_enquiry and enquiry_describe through its focus on field metadata.
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 direct usage guidance: pass answers to submit_enquiry keyed by field key. This tells the agent how to apply the returned data and implies the tool is for fetching field metadata before submission. It does not explicitly mention when not to use it or compare with enquiry_describe, but the context is sufficient.
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 Contractor Pay 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 specialist contractor accountant, 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 specialist contractor accountant, 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, the description carries the full burden and covers it thoroughly: validation, summary and token return, email notification, the recipient's pre-submission click requirement, and exact consent wording. It also warns this is not a purchase or guaranteed quote, which prevents mistaken expectations.
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 dense but every sentence carries necessary workflow, consent, or exclusion information. Key constraints are front-loaded, and the consent quote is included where it matters.
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, consent-gated submission with no output schema and no annotations, the description is complete: agent knows inputs, sequencing, human-facing consent, token handoff, and what happens after submission. Nothing needed to call it correctly appears 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 100%, the description adds workflow meaning: answers must be keyed by enquiry_fields keys, consent must be true and accompanied by the exact consent sentence, and confirmation is the token from step 1 used only after approval. This goes beyond the schema's generic object/boolean/string definitions.
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?
Description begins 'Submits an enquiry to Contractor Pay Calculator' with explicit exclusions 'NOT a purchase, NOT a guaranteed quote', distinguishing it from calculation/purchase tools. The two-step nature is stated up front, so an agent knows exactly what action this tool performs.
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 step-by-step workflow: call once to validate and obtain a token, then call again only if the person agrees, with same answers and consent=true. It tells the agent when not to call and clarifies provider visibility requires an email click, though it doesn't explicitly name sibling alternatives.
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 has a distinct role: calculate runs the calculator, calculator_describe documents it, while enquiry_describe explains the enquiry flow, enquiry_fields provides the schema, and submit_enquiry performs the submission. There is no meaningful overlap or ambiguity between them.
Names are readable and mostly follow a noun-oriented pattern for descriptive tools (calculator_describe, enquiry_describe, enquiry_fields) with action verbs for operations (calculate, submit_enquiry). The main inconsistency is that calculate is a bare verb while calculator_describe reverses the verb-noun order, but this is minor and not confusing.
Five tools is well-scoped for this server's purpose: two calculator-related tools and three enquiry-related tools. Each tool has a clear place and none feel redundant or missing.
The surface fully covers the calculator and enquiry workflow: the calculator can be executed and its assumptions inspected, and the enquiry flow includes process documentation, field schema, and a validated two-step submission with consent. No obvious dead ends or missing operations are apparent.