MCP Europe Tools
Server Details
European data validation tools for AI agents. Validates Portuguese NIF, IBAN for 18 European countries, VAT rates for all EU countries, Portuguese public holidays, and European number formatting.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.5/5 across 11 of 11 tools scored.
All 11 tools have clearly distinct purposes: separate holiday tools for France, Portugal, Spain; distinct validators for different country-specific identifiers (NIF, NIF ES, SIRET, TVA FR, IBAN); plus working days, number formatting, and VAT rates. No two tools could be confused.
Every tool follows a consistent verb_noun pattern in snake_case: 'validate_' for validators, 'get_' for holidays, 'calculate_', 'format_', etc. No mixing of conventions like camelCase or inconsistent verb choice.
With 11 tools covering essential European business operations (holidays for 3 countries, VAT rates, number formatting, working days, and 5 validators), the count is well-scoped. Each tool earns its place without bloat or deficiency.
The set is reasonably complete for its focus on Portugal, Spain, and France, covering the main workflow needs. However, the working days tool is tied to Portuguese holidays only, and there are no tools for other European countries' holidays or currency formatting, leaving minor gaps.
Available Tools
11 toolscalculate_working_daysARead-onlyIdempotentInspect
Counts the number of working days between two dates (inclusive), excluding Saturdays, Sundays, and all 10 Portuguese national public holidays. Returns { start_date, end_date, working_days: number }. Use when calculating Portuguese invoice payment deadlines (30/60/90 days), legal notice periods, project milestones, SLA response times, or any business process governed by Portuguese working days. Input dates must be in YYYY-MM-DD format.
| Name | Required | Description | Default |
|---|---|---|---|
| end_date | Yes | End date in YYYY-MM-DD format, inclusive. Example: '2026-01-31' | |
| start_date | Yes | Start date in YYYY-MM-DD format, inclusive. Example: '2026-01-01' |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds behavioral details beyond annotations: inclusive dates, excluded days (weekends + 10 Portuguese holidays), and return object structure. No contradiction with annotations (readOnlyHint, idempotentHint).
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 concise sentences: first defines the function and scope, second lists use cases. No extraneous content, well-front-loaded.
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?
Even without output schema, description specifies return fields (start_date, end_date, working_days). Includes holiday count detail. Fully adequate for this simple 2-parameter 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% with descriptions including format examples. Description reinforces inclusivity and format but adds minimal new information 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?
Clearly states 'Counts the number of working days between two dates (inclusive)', identifies exclusive holidays (Saturdays, Sundays, Portuguese holidays), and distinguishes from siblings by focusing on Portuguese business context.
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?
Explicitly lists use cases (Portuguese invoice deadlines, legal notice periods, project milestones, SLA) and implies when not to use (non-Portuguese contexts). Also specifies date format requirement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
format_number_europeanARead-onlyIdempotentInspect
Formats a number using the locale conventions of a specific European country, applying the correct decimal separator and thousands separator. Returns { original: number, formatted: string, locale: string, country_code: string }. Different European countries use different conventions — Portugal and most of continental Europe use '1.234,56' (dot as thousands, comma as decimal), while Ireland uses '1,234.56'. Supports PT, ES, FR, DE, IT, NL, BE, PL, SE, DK, FI, AT, IE, GR, HU, RO. Use when displaying prices, measurements, or any numeric value to end users in a specific European country.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | The numeric value to format. Example: 1234.56 | |
| decimals | No | Number of decimal places. Defaults to 2. Use 0 for whole numbers, 2 for prices. | |
| country_code | Yes | Two-letter country code for the target locale. Example: 'PT', 'FR', 'DE' |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses return structure and behavior beyond annotations: returns {original, formatted, locale, country_code} and describes separator conventions for different countries. No contradictions with readOnlyHint/idempotentHint.
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?
Four concise sentences with front-loaded main action, then details on conventions and supported countries. No superfluous content.
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?
Complete description for a formatting tool: explains return structure, contrasts conventions, lists all supported countries (18 codes). No output schema needed as return structure is described.
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?
Adds meaningful examples and usage tips for each parameter (e.g., 'Example: 1234.56', 'Use 0 for whole numbers, 2 for prices') beyond the schema descriptions, which already cover 100%.
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?
Clearly states the tool formats a number using European locale conventions, specifying the resource (number) and action (format). Distinguishes from sibling tools (holidays, VAT, IBAN, etc.) by focusing on number formatting.
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?
Explicitly states when to use: 'when displaying prices, measurements, or any numeric value to end users in a specific European country.' Does not provide when-not or alternatives, but context makes alternatives unnecessary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_france_holidaysARead-onlyIdempotentInspect
Returns all French national public holidays for a given year as a structured list. Each holiday includes { date: 'YYYY-MM-DD', name: string, name_en: string }. Returns 11 mandatory holidays defined by French law. Easter-dependent holidays (Easter Monday, Ascension Thursday, Whit Monday) are dynamically calculated for the requested year using the Anonymous Gregorian algorithm. Use when calculating French business deadlines, delivery dates, or scheduling tasks that must avoid non-working days in France.
| Name | Required | Description | Default |
|---|---|---|---|
| year | Yes | Calendar year as a 4-digit integer. Example: 2026 |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true and idempotentHint=true. The description adds that Easter-dependent holidays are dynamically calculated using the Anonymous Gregorian algorithm, which provides useful behavioral context beyond 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 two sentences, front-loaded with the main purpose, then details. Every sentence earns its place without 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 simple lookup tool with one parameter and no output schema, the description adequately explains output structure and special calculation. It could mention error handling for invalid years, but overall sufficient.
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 single parameter 'year' has 100% schema coverage with description 'Calendar year as a 4-digit integer. Example: 2026'. The tool description does not add new semantics beyond what the schema already provides.
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 returns French national public holidays for a given year as a structured list with specific fields. It distinguishes from sibling tools like get_portugal_holidays by focusing on France.
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: 'Use when calculating French business deadlines, delivery dates, or scheduling tasks that must avoid non-working days in France.' It does not explicitly state when not to use, 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.
get_portugal_holidaysARead-onlyIdempotentInspect
Returns all Portuguese national public holidays for a given year as a structured list. Each holiday includes { date: 'YYYY-MM-DD', name: string, name_en: string }. Returns 10 mandatory national holidays defined by Portuguese law. Use when calculating business deadlines, delivery dates, payment due dates, SLA periods, or scheduling tasks that must avoid non-working days in Portugal. Does not include municipal or regional holidays (e.g. Lisbon June 13, Porto June 24) which vary by city.
| Name | Required | Description | Default |
|---|---|---|---|
| year | Yes | Calendar year as a 4-digit integer. Example: 2026 |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context beyond annotations (readOnlyHint, idempotentHint) by specifying it returns exactly 10 mandatory national holidays and the output structure. It does not contradict any annotations; it aligns with read-only, idempotent behavior.
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 concise, well-structured, and front-loaded with purpose. Each sentence provides distinct value: purpose, output structure, usage cases, and exclusions. 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?
Given the tool's simplicity (one parameter, no output schema), the description is fully complete. It explains what is returned, when to use it, and what is excluded, leaving no gaps for an AI agent to misunderstand.
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 100% coverage with clear description and example for the single parameter 'year'. The description does not add substantial new meaning beyond what the schema already provides, so baseline score of 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 clearly states the tool returns Portuguese national public holidays for a given year, with a structured list including date, name, and English name. It differentiates itself from sibling tools like get_france_holidays and get_spain_holidays by specifying the country and scope (only national, not municipal).
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?
Explicitly states when to use the tool: for calculating business deadlines, delivery dates, payment due dates, SLA periods, or scheduling tasks avoiding non-working days. It also clarifies what is not included (municipal/regional holidays) with examples, guiding the agent away from inappropriate uses.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_spain_holidaysARead-onlyIdempotentInspect
Returns all Spanish national public holidays for a given year as a structured list. Each holiday includes { date: 'YYYY-MM-DD', name: string, name_en: string }. Returns 9 mandatory national holidays defined by Spanish law. Use when calculating business deadlines, delivery dates, or scheduling tasks that must avoid non-working days in Spain. Does not include regional holidays that vary by autonomous community (Catalonia, Madrid, Andalusia, etc.) — only nationally mandated holidays are returned.
| Name | Required | Description | Default |
|---|---|---|---|
| year | Yes | Calendar year as a 4-digit integer. Example: 2026 |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the core behavioral traits are covered. The description adds useful context: returns exactly 9 holidays, excludes regionals, and provides the output format. No contradiction with 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?
Two sentences with no wasted words. First sentence states core functionality and output format. Second sentence provides usage guidance and exclusion. Efficient and front-loaded.
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 the tool's simplicity (one param, no output schema, annotations present), the description covers purpose, return format, usage, and limitations. It does not mention error handling for invalid years, but that is a minor 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?
The single parameter 'year' is fully described in the schema (100% coverage) with type, description, and example. The description does not add additional meaning beyond that, but baseline 3 is appropriate as schema does the work.
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 it returns Spanish national public holidays for a given year, specifies the output format (date, name, name_en), and mentions it returns exactly 9 mandatory holidays. This uniquely identifies its purpose and differentiates it from sibling tools like get_france_holidays.
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 usage guidance: use when calculating business deadlines, delivery dates, or scheduling tasks avoiding non-working days. It also explicitly states what the tool does NOT include (regional holidays), helping the agent avoid misuse.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_vat_rateARead-onlyIdempotentInspect
Returns all VAT (Value Added Tax) rates for a given EU country — standard, reduced, intermediate, and super-reduced rates where applicable, as numeric percentages. Returns { country, standard, reduced?, intermediate?, superreduced? } for supported countries, or { error, available } listing all valid codes if the country is not found. Supports 18 EU member states: PT, ES, FR, DE, IT, NL, BE, PL, SE, DK, FI, AT, IE, GR, HU, RO, CZ, HR. Use when calculating EU cross-border invoice tax, determining correct rate for e-commerce checkout by customer country, generating compliant VAT breakdowns, or any workflow requiring accurate and current EU VAT rates per jurisdiction.
| Name | Required | Description | Default |
|---|---|---|---|
| country_code | Yes | Two-letter ISO 3166-1 alpha-2 country code. Example: 'PT' for Portugal, 'FR' for France, 'DE' for Germany |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and idempotentHint, indicating safe read operation. The description adds that an error object with available codes is returned for unsupported countries, which is valuable beyond 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 concise (4 sentences) and front-loaded with the main purpose. It efficiently includes output shape, supported countries, and use cases without 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 simple tool with one parameter and no output schema, the description is complete. It covers both success and error scenarios, lists all 18 supported country codes, and explains the output structure. No 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?
Only one parameter 'country_code' with 100% schema description including examples. The description adds context by listing supported countries and explaining error handling, which supplements the schema meaningfully.
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 it returns VAT rates for a given EU country, listing specific rate types and the output format. It distinguishes itself from sibling tools (holidays, validation, calculation) by its specific tax-rate 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?
Explicitly states when to use: 'Use when calculating EU cross-border invoice tax...' providing clear context. However, it does not explicitly state when NOT to use it (e.g., for non-EU countries or historical rates), but the positive guidance is strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_ibanARead-onlyIdempotentInspect
Validates an IBAN (International Bank Account Number) using the ISO 13616 MOD-97 algorithm. Supports 18 European countries: PT, ES, FR, DE, IT, NL, BE, PL, SE, DK, FI, AT, IE, GR, HU, RO, CZ, HR. Returns { valid: boolean, country: string, iban: string } — country is extracted from the 2-letter prefix. Returns { valid: false, reason: string } for malformed input. Spaces are automatically stripped before validation. Use when validating supplier bank details for SEPA transfers, processing direct debit mandates, verifying payment data in e-commerce checkouts, or any workflow requiring a verified EU bank account number. Validates structure and checksum only — does not confirm account existence.
| Name | Required | Description | Default |
|---|---|---|---|
| iban | Yes | European IBAN with or without spaces. Example: 'PT50 0002 0123 1234 5678 9015 4' or 'PT50000201231234567890154' |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint=true. Description adds behavioral details: automatic space stripping, return format for success and failure, and validation scope (structure and checksum only). No contradictions.
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?
Description is a single paragraph with multiple sentences, but each sentence adds value (algorithm, countries, return format, use cases, limitations). Could be slightly more concise but remains well-structured.
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 single-parameter tool with no output schema, the description thoroughly explains behavior, return values, supported countries, and limitations. It is fully self-contained and leaves no ambiguity.
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% with one parameter. Description adds example value, explains spaces are allowed and stripped, and provides context about algorithm and countries, significantly enriching 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?
Description clearly states 'validates an IBAN' using ISO 13616 MOD-97 algorithm, lists supported countries, and distinguishes from sibling tools like validate_nif and validate_siret by focusing on IBAN validation.
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?
Explicitly specifies use cases (SEPA transfers, direct debit mandates, e-commerce checkouts) and what it does not do ('does not confirm account existence'), providing good context. Does not explicitly name alternatives but siblings are distinct enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_nifARead-onlyIdempotentInspect
Validates a Portuguese NIF (Número de Identificação Fiscal) — the 9-digit tax identification number issued by the Portuguese Tax Authority (AT) to individuals and companies. Applies the official modulo-11 checksum algorithm to verify the check digit. Returns { valid: true, nif: string } for valid NIFs, or { valid: false, reason: string } for invalid format or failed checksum. First-digit rules are enforced: 1–3 for individuals, 5 for corporations, 6 for public entities, 7–8 for other entities, 9 for occasional taxpayers. Use when processing Portuguese invoices (faturas), onboarding suppliers, validating user registrations, or any fiscal compliance workflow. Does not query the AT database — offline format and checksum validation only.
| Name | Required | Description | Default |
|---|---|---|---|
| nif | Yes | 9-digit Portuguese NIF, with or without spaces. Example: '123456789' or '123 456 789' |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds that validation is offline (no AT database query), which is valuable context. No contradictions.
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 sentences, front-loaded with purpose, then details, then use cases. Every sentence adds distinct value—no fluff.
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?
Covers return format, algorithm, first-digit rules, use cases, and limitations. No output schema, but return values are explicitly described. Complete for the tool's complexity.
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 has 100% coverage with a description. The description adds examples and flexibility note ('with or without spaces'), enhancing the schema's value.
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 tool validates a Portuguese NIF using the modulo-11 checksum, specifies return format, and mentions first-digit rules. It distinguishes from sibling tools like validate_nif_es by specifying country and entity types.
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?
Explicitly lists use cases (Portuguese invoices, supplier onboarding, user registration) and states the limitation ('Does not query the AT database'), helping the agent decide when to use and when not to.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_nif_esARead-onlyIdempotentInspect
Validates Spanish tax identification numbers — NIF (DNI, 8 digits + check letter, for Spanish citizens), NIE (Número de Identidad de Extranjero, starts with X/Y/Z, for foreign residents), and CIF (Código de Identificación Fiscal, letter + 7 digits + control, for companies). Automatically detects the document type. Returns { valid: boolean, type: 'NIF'|'NIE'|'CIF', id: string }. Use when processing Spanish invoices, e-commerce orders, supplier registrations, or any document requiring a verified Spanish fiscal identifier.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Spanish NIF, NIE or CIF with or without spaces. Examples: '12345678Z' (NIF), 'X1234567L' (NIE), 'B12345678' (CIF) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, and the description adds auto-detection of document type and return format, enhancing transparency without contradiction.
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?
Extremely concise: two sentences covering purpose, types, and use cases with 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 simple tool with one parameter and no output schema, the description explains return structure and covers all necessary 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?
Schema coverage is 100% with description for the single parameter; the description adds examples and clarification of accepted formats (with/without spaces, types like '12345678Z').
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 it validates Spanish tax IDs (NIF, NIE, CIF) with specific definitions for each type, distinguishing it from sibling tools like validate_nif and validate_iban.
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 usage contexts (Spanish invoices, orders, registrations) but does not mention when not to use or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_siretARead-onlyIdempotentInspect
Validates a French SIRET (Système d'Identification du Répertoire des Établissements) number using the official Luhn algorithm. SIRET is a 14-digit number — the first 9 digits are the SIREN (company identifier) and the last 5 digits identify the specific establishment. Returns { valid: boolean, siren: string, establishment: string, siret: string }. Use when processing French invoices (factures), validating supplier registrations, or any B2B transaction requiring a verified French business establishment identifier. Handles the La Poste special case automatically.
| Name | Required | Description | Default |
|---|---|---|---|
| siret | Yes | 14-digit French SIRET, with or without spaces/dashes. Example: '732 829 320 00074' or '73282932000074' |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint and idempotentHint, indicating a safe, repeatable operation. The description adds the La Poste special case handling and the exact return shape (valid, siren, establishment, siret), providing useful behavioral context beyond the 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 three concise sentences, each serving a clear purpose: action/algorithm, structure explanation, and usage context. Information is front-loaded, with 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?
Despite lacking an output schema, the description explicitly defines the return object. The single parameter is well-documented. The tool is simple, and the description covers purpose, algorithm, usage, special case, and return format comprehensively.
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 schema describes the parameter format. The description adds meaning by explaining SIRET structure (SIREN + establishment digits) and mentioning automatic La Poste handling, which is not in 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 the tool validates a French SIRET number using the Luhn algorithm. It explicitly mentions the identifier type and algorithm, making the purpose distinct from siblings like validate_iban or validate_nif.
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 clear use cases: processing French invoices, validating supplier registrations, or B2B transactions requiring a verified French business identifier. It does not explicitly state when not to use it or name alternatives, but sibling tools imply alternatives exist.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_tva_frARead-onlyIdempotentInspect
Validates a French TVA intracom (VAT) number — the EU VAT identifier for French companies. Format is 'FR' + 2 alphanumeric key characters + 9-digit SIREN. Returns { valid: boolean, key: string, siren: string, tva: string }. When the key is numeric, validates using the official formula: key = (12 + 3 × (SIREN mod 97)) mod 97. Use when validating French supplier VAT numbers, processing cross-border EU invoices, or any intra-EU transaction requiring a verified French VAT identifier.
| Name | Required | Description | Default |
|---|---|---|---|
| tva | Yes | French TVA intracom number with or without spaces. Example: 'FR 40 303 265 045' or 'FR40303265045' |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and idempotentHint. Description adds validation formula details and specific return values, enhancing transparency beyond annotations. No contradictions.
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?
Description is concise with no waste: each sentence adds value—purpose, format, logic, and usage context. Front-loaded with the action and outcome.
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?
Single parameter, no output schema, but return fields are listed. Description covers validation logic and typical use cases. Slightly lacking in output format details (e.g., types) but sufficient given simplicity.
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 covers 100% of parameters with a description for 'tva'. Description adds format examples and explains the key validation formula, providing additional practical guidance.
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 clearly states it validates a French TVA number, specifies the exact format (FR + 2 key + 9-digit SIREN), and lists return fields. This distinguishes it from sibling tools like validate_iban or validate_nif.
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?
Explicitly recommends use for validating French supplier VAT numbers, cross-border EU invoices, or intra-EU transactions. No negative guidance or alternatives mentioned, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
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Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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