Free EU VAT (VIES) + pan-EU company data (10 registers), payable in EURC/USDC via x402.
List the EU company registers currently covered by lookup_eu_company / the paid eu-company endpoint, with each register's country, source, licence, whether officers are returned, and the identifier format. FREE. Call this to discover coverage before paying.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description clearly states the tool is FREE and lists the fields returned, indicating a read-only listing operation. Lack of rate limit or pagination info is acceptable for a simple list with no parameters.
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, front-loaded with the main action. Every sentence adds value: first sentence defines output, second sentence gives usage guidance. 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?
Given no output schema, the description adequately explains return fields and usage context. It is complete for a list tool without parameters, covering all necessary information.
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?
Input schema has zero parameters, so schema coverage is 100%. The description adds context about what is listed (countries, sources, licences, etc.) without needing to explain 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 clearly states the tool lists EU company registers covered by the paid endpoint, specifying the details returned (country, source, licence, officers, identifier format). It distinguishes itself from siblings by referencing lookup_eu_company and validate_eu_vat.
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 says 'Call this to discover coverage before paying', providing clear guidance on when to use the tool (before paying for the paid endpoint). It implies not to use for actual lookups.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Detect the jurisdiction of a company registration number for FREE across 10 EU registers (no, fr, fi, sk, gb, lv, ro, ee, cz, pl). The FULL normalized record (legal name, status, legal form, registered address, incorporation date, officers, provenance) is a PAID x402 service (EUR 0.05/call in EURC or USDC on Base) — this tool returns the exact paid endpoint, price, and how to pay.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Company/registration number: SIREN (FR), org.nr (NO), Y-tunnus (FI), IČO (SK), company number (UK), regcode (LV), CUI or J-number (RO). | |
| country | No | Optional ISO country code to disambiguate; otherwise auto-detected from the id. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description partially covers behavior: it notes the free detection and paid endpoint info. But it does not mention error handling, rate limits, or what happens on invalid IDs.
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, fairly concise. It front-loads the key benefit (free detection) but could be structured more cleanly with bullet points or shorter clauses.
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 description omits details on the free detection output format and error states. Given no output schema, more completeness would be beneficial for an agent to correctly invoke and interpret the 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% and contains detailed parameter descriptions. The tool description does not add further parameter semantics beyond what the schema already provides, meeting the baseline.
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 detects jurisdiction for free and provides info on the paid full record. It distinguishes itself from siblings by focusing on company lookup vs list or VAT 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?
The description explains the free detection and paid record option, giving context on when to use. However, it does not explicitly contrast with siblings or state prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Validate an EU VAT number against the official EU VIES registry. FREE. Returns whether the number is currently valid and, when the member state discloses it, the registered company name and address. Covers all 27 EU member states.
| Name | Required | Description | Default |
|---|---|---|---|
| vat | Yes | EU VAT number: 2-letter country code + number, e.g. IT08714440016. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description adds useful context: it returns validity and optional company info, is free, covers 27 countries. However, it does not mention side effects, authentication needs, or error conditions, leaving some behavioral gaps.
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 concise sentences, no wasted words, front-loads the action and key attributes (free, coverage).
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 description covers the main purpose, input, and output for a simple read tool, but could mention potential errors or limitations (e.g., network dependency, member state disclosure variability).
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 schema already provides 100% coverage with a description of the single parameter; the tool description adds an example format but does not significantly enhance understanding 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?
The description clearly states the tool's action ('Validate an EU VAT number') against a specific resource (VIES registry), distinguishes from siblings like list_supported_countries and lookup_eu_company, and adds details about being free and covering all EU member states.
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 context for when to use (validating EU VAT numbers) and implies alternatives via sibling tools, but does not explicitly state when not to use or list specific exclusion scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as io.github.alice/server, link the matching GitHub user or an account that owns the GitHub organization, then choose Claim with GitHub.
HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at /.well-known/glama.json on the same origin as the connector, then choose Check HTTP challenge.
DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
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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European business verification for AI agents: registry, VAT, sanctions, IBAN. Pay-per-call x402.
11.3M entities, 10 countries, 12 tools. EU VAT (VIES), BORME, GLEIF, KYB. Free: 100 req/month.
Deterministic IBAN/LEI/VAT/SWIFT/rental-fraud checks via MCP; x402 USDC per call, signed receipts.
SLA'd EU VAT validation on VIES. Honest 3-state result, never guesses. 100 free lookups.
Add one secure layer between your agents and this server.
Each tool has a distinct purpose: listing supported countries, looking up a company (with a free jurisdiction detection and a paid full record), and validating EU VAT numbers. No overlap in functionality.
All tool names follow a consistent verb_noun pattern in snake_case: list_supported_countries, lookup_eu_company, validate_eu_vat. Easy to predict and read.
Three tools is appropriate for the domain of EU compliance covering VAT validation and company data lookup. Neither too few nor too many.
The set covers key operations: discovering coverage, detecting jurisdiction, and validating VAT. A minor gap is the lack of a tool to directly handle the paid service, but the descriptions guide the user externally.