Server Details
Redundancy Calculator Ireland: the site's own MCP server — calculator, enquiry (enquiry = a...
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
5 toolscalculateStatutory redundancy calculatorAInspect
Run the Statutory redundancy calculator calculator: Weekly pay used (capped at €600); Weeks of pay due (2 per year + 1); Statutory redundancy lump sum. Missing inputs fall back to their documented defaults.
| Name | Required | Description | Default |
|---|---|---|---|
| years | No | Years of continuous service | |
| weeklyPay | No | Gross weekly pay |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden and does a solid job: it discloses the €600 weekly pay cap, the '2 per year + 1' weeks formula, the lump-sum output, and the default-fallback behavior. This is meaningful behavioral context beyond the schema.
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 filler and front-loads the action. The minor typo 'calculator calculator' is a small blemish but does not hurt comprehension.
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 2-parameter calculator with no output schema, the description covers the essential computation rules, the cap, and fallback behavior. It doesn't specify the exact output structure, but that is less critical for a calculator 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?
Schema coverage is 100%, so the baseline is 3. The description adds real value by explaining the weekly-pay cap applied to weeklyPay and the formula relating years to weeks of pay, which the schema alone does not convey.
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 concrete action ('Run the calculator') and specifies the resource ('Statutory redundancy calculator') along with the core calculations it produces. It is clear enough for an agent to know the tool performs redundancy lump-sum calculations, though it doesn't 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 description implies its use case: when a statutory redundancy amount needs to be computed. However, it gives no explicit guidance about when not to use it or which sibling tool to prefer, such as calculator_describe for mere explanation rather than calculation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculator_describeWhat Statutory redundancy 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 disclosure burden. It openly says the tool returns inputs, outputs, assumptions, and tables, making its informational, read-only nature clear. It does not detail response format or side effects, but none are expected for a describe 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?
The description is one tight phrase with no filler, listing the three relevant content categories. It loses a point for being a sentence fragment that slightly overlaps with the title rather than stating the tool's action directly.
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 parameterless, documentation-style tool, the description covers the key things an agent needs: what the tool returns and the scope of the calculator. It could be more complete by mentioning that actual calculations belong to the calculate sibling and by describing the return format, but these are minor 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 tool has zero parameters, so the schema leaves nothing to explain; per rubric the baseline is 4. The description also adds useful context about the calculator's parameter characteristics (units, ranges, defaults), even though those are not tool parameters.
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 (the Statutory redundancy calculator) and enumerates the content returned: inputs with units/ranges/defaults, outputs, assumptions, and tables. It is clear but does not explicitly differentiate itself from sibling tools such as calculate or 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 intended use is implied: an agent needing to know the calculator's inputs, outputs, assumptions, or underlying tables can call this tool. However, it never states when to use this instead of calculate or enquiry_describe, nor does it mention 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 Redundancy Calculator Ireland: 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 full burden of behavioral disclosure, and it delivers: it states the tool is non-transactional ('Nothing is bought, ordered or paid'), free, guarantees no quote, and documents exactly what the tool returns. This is exemplary transparency for a meta-informational 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?
The structure is well front-loaded with 'Read first,' but the description repeats content already present in the title: 'not a purchase, not a guaranteed quote' mirrors 'Nothing is bought... no quote is guaranteed.' The description earns its place overall, but could be tightened by one clause.
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 0-parameter informational tool with no output schema and no annotations, the description is complete: it conveys the tool's nature, what underlying operation it documents, and the contents of its return value. Nothing an agent needs to call it correctly 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 0 parameters, so the baseline is 4. There is no parameter meaning to add; the description correctly focuses on what the tool itself returns rather than 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 states a specific purpose: it is an informational tool that explains what submit_enquiry does on Redundancy Calculator Ireland, and lists what it returns (recipient details, consent wording, confirmation mechanism). This clearly distinguishes it from its siblings — it is the 'describe' companion to submit_enquiry, mirroring the calculator_describe pattern.
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 directive 'Read first' gives clear context that this tool should be consulted before engaging with the enquiry workflow. It doesn't explicitly name alternatives or state when-not-to-use, but the leading instruction is a strong usage signal.
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 Redundancy Calculator Ireland 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 and does add value by disclosing which field attributes are returned and how keys map to submit_enquiry. However, it doesn't explicitly state that the operation is read-only, describe the response format, or note edge cases (e.g., empty field set). No contradiction, since annotations are absent.
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 that front-loads the core resource ('Every field of the Redundancy Calculator Ireland enquiry'), then lists the attributes and the follow-up action in order. No filler or 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 tool with no annotations and no output schema, the description covers the essentials: what is returned, what the attributes are, and how the result is used with submit_enquiry. The only notable gap is the lack of explicit differentiation from the sibling enquiry_describe, which is a minor omission for a tool this simple.
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 meaning beyond the empty schema by explaining what each returned field attribute represents and how the keys are used downstream, which helps the agent interpret and subsequently use the output.
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 resource — the fields of the Redundancy Calculator Ireland enquiry — and enumerates the exact content returned (key, label, type, required, help text, allowed options). It partially distinguishes itself by referencing sibling submit_enquiry, though it never explicitly contrasts with 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?
Implied usage: 'Pass answers to submit_enquiry keyed by field key' conveys the workflow the output feeds into, so an agent can infer this tool is meant for discovering submission keys. However, it never explicitly says when to use this tool versus alternatives like enquiry_describe, and no exclusions are stated.
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 Redundancy Calculator Ireland — 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 relevant employment solicitor or tax adviser, 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 relevant employment solicitor or tax adviser, 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 the full behavioral burden and does so thoroughly: it discloses validation, returned summary, consent line, confirmation token, the required second confirmation call, and the email verification step before provider visibility. No annotation contradiction exists.
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 earns its place, front-loading the critical caveat that this is not a purchase or guaranteed quote and explicitly labeling Step 1 and Step 2. It is long only because the two-step workflow itself requires those details.
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, the description supplies all necessary operational context: how to start, what step 1 returns, when to proceed, what step 2 requires, and the downstream email behavior. The reference to enquiry_fields also resolves where parameter keys come from.
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%, and the description enriches the parameters: it explains answers are keyed by field key from enquiry_fields, repeats the exact consent wording, and specifies that confirmation is the token from step 1. This adds workflow meaning beyond the bare 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 opens with a specific verb and object (Submits an enquiry to Redundancy Calculator Ireland) and immediately distinguishes the tool from a purchase or guaranteed quote. The title's two-step phrasing reinforces the differentiation, so an agent can separate it from the calculation and description 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?
It provides an explicit two-step protocol: first call with answers and consent=true to get a summary and token, then call again with the token only after the person agrees. It also states the condition for consent and what happens after submission (email link required before providers see it), leaving no ambiguity about when to invoke the tool.
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 clearly distinct role: running the calculator, describing the calculator, explaining the enquiry process, providing the enquiry field schema, and submitting the enquiry. There is no meaningful overlap between tools.
Names are readable and consistently snake_case, but the verb/noun pattern is mixed: calculate and submit_enquiry are verb-first, while calculator_describe and enquiry_describe are noun-first, and enquiry_fields is noun-noun. This is not chaotic, but it lacks a single predictable convention.
Five tools is well-scoped for a focused statutory redundancy calculator with an enquiry submission workflow. Each tool covers a distinct part of the user journey without redundancy or bloat.
The set covers the full lifecycle: computing a redundancy payment, understanding the calculator, understanding the enquiry process, retrieving the exact form fields, and submitting with consent. There are no obvious missing operations that would strand an agent.