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Server Details
Malta VAT Registration: the site's own MCP server — checker, enquiry (enquiry = a human handoff,...
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
6 toolschecker_answerAnswer a question, get the next stepBInspect
Given a question id and the chosen option (its choice index), return the next question or the final verdict.
| Name | Required | Description | Default |
|---|---|---|---|
| choice | Yes | ||
| question | Yes |
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. It mentions the return value ('next question or final verdict') but does not disclose whether the answer is recorded, whether state changes, whether calls are idempotent, or any side effects of answering.
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, focused sentence with no redundant phrases. It front-loads the core behavior and avoids unnecessary detail.
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, no annotations, and no parameter descriptions, the description is too sparse. It leaves unclear the exact input format, side effects, response structure, and how this fits into the broader checker flow alongside siblings like checker_start and checker_tree.
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 0%, so the description must compensate. It adds useful meaning by identifying 'question' as a question id and 'choice' as the option index. However, it does not explain the format of the question id, how to obtain valid values, or the expected range of choice beyond the schema's minimum of 0.
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 the action: given a question and a choice index, return the next question or final verdict. It identifies the resource and expected output, but it does not explicitly differentiate itself from sibling tools like checker_start or checker_tree.
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 phrase 'Given a question id and the chosen option' implies use after a question has been presented and an option selected. However, there is no explicit guidance on when to use this tool versus the sibling tools, nor any exclusions or alternative routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
checker_startStart: Malta VAT registration checkerBInspect
The first question of the Malta VAT registration checker decision guide.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of explaining behavior. It only says that this is 'the first question' of a decision guide, which implies a read-only presentation of a question but does not disclose whether state is created, whether the guide can be restarted, what the response contains, or any 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 concise sentence that adds useful information beyond the title ('first question') without any filler or repetition. It is appropriately sized for such a simple tool.
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 is low-complexity with no parameters, so the description is minimally sufficient to justify calling it first. However, there is no output schema and no mention of what the response will look like or how to proceed after receiving the first question, which leaves the agent without explicit next-step guidance.
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 nothing for the description to clarify about parameter meaning. The baseline for a zero-parameter tool is 4, and the description correctly adds no unnecessary parameter details.
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 tool as 'the first question' of a specific decision guide, which clearly signals it is the entry point. It distinguishes itself from sibling tools like checker_answer and checker_tree by establishing its position at the start of the flow, though it lacks an explicit verb like 'starts' or 'returns'.
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 phrase 'first question' implies that this tool should be called at the beginning of the Malta VAT registration checker flow, and that checker_answer or checker_tree would be used afterwards. However, it does not explicitly state when to use this tool versus its siblings or mention any conditions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
checker_treeThe whole decision treeAInspect
Every question, option and verdict of the Malta VAT registration checker guide, for reasoning end to end.
| 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 disclosure. It accurately reveals the tool's content scope ('every question, option and verdict') but does not describe the output format, size, or whether it is a static snapshot. This is a moderate disclosure for a read-like tool without annotations.
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, front-loaded sentence that states the subject, scope, and intended purpose without any filler. Every phrase contributes to the agent's understanding.
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 tool with no output schema, the description provides the key facts: it returns the complete decision tree of the checker guide for end-to-end reasoning. It could add structure details, but the current content is sufficient for an agent to decide to call it and know what it will receive.
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 no properties and schema description coverage is 100%, so there are no parameters to document. The baseline for zero-parameter tools applies; the description adds no parameter semantics but none are needed.
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 a specific resource (the Malta VAT registration checker guide) and explicitly states its scope: every question, option, and verdict in the decision tree. This clearly distinguishes it from sibling tools such as checker_answer or checker_start, which handle individual steps or starting points.
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 phrase 'for reasoning end to end' gives a clear context for when an agent should use this tool: when the full decision tree is needed, not a single answer. It does not explicitly list exclusions or alternative tool names, but the usage context is sufficiently implied.
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 Malta VAT Registration: 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. It clearly states this is informational: it describes what submit_enquiry does, emphasizes that nothing is bought, ordered, or paid, notes no quote is guaranteed, and says it is free. It also reveals what the call returns (recipient details, consent wording, confirmation method), though it does not explicitly say 'this call performs no external 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 tight and front-loaded: it opens with the imperative 'Read first', then delivers the essential facts in two sentences. Every clause adds value—scope, non-purchase, free, non-guaranteed, and output contents—with 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 zero-parameter, no-output-schema informational tool, the description is complete: it tells the agent what the tool does, what content it returns, and the key limitations. There are no missing parameters or return-value expectations that an agent would need to call it 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?
The tool has zero parameters and an empty input schema, so there are no parameter semantics to clarify. Per the baseline rule for zero-parameter tools, a score of 4 applies since the schema fully covers the call signature and the description adds no parameter-related confusion.
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 a specific verb and resource: it 'states plainly what submit_enquiry does' on Malta VAT Registration, clearly identifying the tool as a descriptive companion rather than the action itself. The title reinforces the non-transactional scope ('not a purchase, not a guaranteed quote'), and the description distinguishes it from submit_enquiry by clarifying nothing is bought, ordered, or paid.
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 explicitly says 'Read first', which instructs the agent to consume this tool before calling submit_enquiry. It provides clear context for when to use the description tool, though it does not explicitly contrast it with the checker_* siblings or state when not to use them.
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 Malta VAT Registration 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 burden of disclosing behavior. It clearly implies a read-only metadata retrieval operation by describing the field attributes returned, and the instruction to pass answers to submit_enquiry emphasizes that this tool itself does not submit. It does not explicitly state side effects or auth, but for a simple zero-parameter getter the behavior is adequately transparent.
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 dense, front-loaded sentences with no wasted words. The first sentence states the resource and output fields; the second sentence gives a direct usage hint. 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?
For a simple zero-parameter introspection tool, the description covers the key information: what fields are listed and how the output should be used with submit_enquiry. It does not specify the exact return container (array vs object), but the list of attributes and the keyed-answers hint give enough context for an agent to proceed.
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 needs to explain no parameters, and it appropriately focuses on the output rather than 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 identifies the resource ('Every field of the Malta VAT Registration enquiry') and enumerates exactly what is returned: key, label, type, required, help text, and allowed options. This differentiates it from siblings like submit_enquiry and checker_start by focusing 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 gives clear usage context by instructing 'Pass answers to submit_enquiry keyed by field key,' linking this tool to the submission workflow. It does not explicitly contrast with alternatives like enquiry_describe, but the intended usage is obvious from the field-key connection.
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 Malta VAT Registration — 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 Maltese VAT practitioner or 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 relevant Maltese VAT practitioner or 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 does well: it discloses that the first call is only validation, that a second call is required to submit, that the response includes a summary/consent line/token, and that the person must click an emailed link before a provider sees anything. No annotation contradiction exists because no annotations were provided.
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 organized into numbered steps, front-loads the essential 'NOT a purchase/quote' caveat, and every sentence adds operational guidance. The consent quote is repeated from the schema, but that repetition is justified because it must be shown verbatim to the person.
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 submission tool with no output schema, the description is complete: it defines the state transition (validation token → confirmed submission), states what is returned, explains the email-link gating, and gives the exact consent text. The nested answers object and optional confirmation parameter are both contextualized in the workflow.
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 covers all three parameters, so the baseline is 3. The description adds meaningful sequencing—answers must key off enquiry_fields, the confirmation token comes from step 1, and the second call must reuse the same answers—and repeats the exact consent wording the agent must show. This modestly exceeds baseline, though schema coverage is already high.
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 verb and resource ('Submits an enquiry to Malta VAT Registration') and explicitly frames it as a two-step workflow rather than a purchase or guaranteed quote. This clearly distinguishes it from the sibling checker/enquiry tools even without naming them.
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 a precise two-step protocol: first call with answers and consent=true, show the returned summary/consent line, then call again with the same answers, consent=true, and the confirmation token only if the person agrees. It also says what the tool is not ('NOT a purchase, NOT a guaranteed quote'). It does not explicitly name alternative sibling tools beyond referencing enquiry_fields as the source of field keys, so it stops short of a full alternatives comparison.
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.
6 tool updates
- First observed
checker_answer - First observed
checker_start - First observed
checker_tree - First observed
enquiry_describe - First observed
enquiry_fields - First observed
submit_enquiry
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TDQS
The tool set splits cleanly into two domains: the Malta VAT registration checker flow (start, answer, tree) and the enquiry form (describe, fields, submit). Each tool has a distinct role with no meaningful overlap, so an agent can reliably select the right one.
Most tools follow a clear resource_prefix + action pattern, such as checker_start, checker_answer, enquiry_describe, and enquiry_fields. The main deviation is submit_enquiry, which reverses the word order, but the naming remains readable and predictable overall.
Six tools is a well-scoped set for the server's purpose: three for the checker decision guide and three for the enquiry workflow. Each tool earns its place and there is no bloat or missing scaffolding.
The checker tools fully cover the decision guide lifecycle: start, step through answers, and inspect the entire tree. The enquiry tools cover discovery, schema, and two-step confirmation submission, leaving no obvious dead ends in the intended workflow.