PESEL/NIP/REGON Validator
Server Details
Validates Polish PESEL, NIP, and REGON checksums; PESEL also decodes birth date and sex.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
TDQS
Each tool targets a distinct Polish identification number type (NIP, PESEL, REGON) with no functional overlap. The descriptions clearly differentiate their validation logic and outputs.
All tool names follow a consistent pattern: the identifier type in lowercase plus '_validate'. This uniform verb_noun structure makes the tool purpose immediately clear.
Three tools perfectly scope the server's purpose as a focused Polish ID validator. Each tool serves a distinct, well-defined function without redundancy.
The server covers all three primary Polish identification numbers (NIP, PESEL, REGON) that commonly require validation. There are no obvious missing identifiers for this specific domain.
Available Tools
3 toolsnip_validateAInspect
Validates the checksum of a 10-digit Polish tax identification number (NIP). Checksum uses weights 6 5 7 2 3 4 5 6 7 over the first 9 digits; sum mod 11 must equal the 10th digit. A sum mod 11 of 10 is itself invalid.
| Name | Required | Description | Default |
|---|---|---|---|
| value | Yes | digits-only identifier to validate (no spaces or dashes) |
Output Schema
| Name | Required | Description |
|---|---|---|
| valid | Yes | |
| reason | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It fully reveals the checksum algorithm and input format constraints, but stops short of stating whether the tool throws exceptions or returns a boolean, which would be ideal for a validation 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?
Three concise sentences, each earning its place: purpose, algorithm, and an edge-case. No superfluous 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 simple tool (1 parameter, no nested objects, single purpose) and the presence of an output schema (which would document return type), the description is complete and leaves minimal ambiguity for the agent.
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 well-described parameter. The description adds value by specifying 'digits-only' and 'no spaces or dashes' beyond the schema, but baseline is 3 per guidelines since schema already covers the parameter well.
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?
Uses specific verb 'validates' and resource '10-digit Polish tax identification number (NIP)', clearly distinguishing it from sibling tools like pesel_validate and regon_validate.
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?
Description explicitly covers when to use (validating a NIP), and sibling tools provide context for alternatives (PESEL, REGON). The algorithm details help the agent reason about correctness.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pesel_validateAInspect
Validates the checksum of an 11-digit Polish national identification number (PESEL). Checksum uses weights 1 3 7 9 1 3 7 9 1 3 over the first 10 digits; control digit is (10 - sum mod 10) mod 10. On success also decodes the date of birth and sex embedded in the number; a checksum-valid number with an impossible calendar date (e.g. Feb 30) is still reported invalid.
| Name | Required | Description | Default |
|---|---|---|---|
| value | Yes | digits-only identifier to validate (no spaces or dashes) |
Output Schema
| Name | Required | Description |
|---|---|---|
| sex | No | |
| valid | Yes | |
| reason | No | |
| birthDate | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It discloses the checksum algorithm, date-of-birth and sex decoding on success, and the special invalid-date condition. However, it omits other behavioral aspects like what happens with incorrect length or non-digit inputs, or whether it checks real assignment.
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 relatively concise—one dense sentence covering purpose, algorithm, and outcomes. It could be improved by splitting into shorter sentences for readability, but it wastes no words and front-loads the core function.
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 it has only one parameter and an output schema (implied by mention of decoded data), the description covers validation logic, success behavior, and an edge case (invalid date). It is missing details on input length validation and what errors are returned for malformed inputs.
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 parameter description states 'digits-only identifier'. The tool description enriches this by specifying the context (Polish national ID), required length (11 digits), and the exact validation logic, adding significant meaning 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 explicitly names the resource (PESEL) and action (validates checksum), specifies it's an 11-digit Polish national ID, and details the algorithm. This clearly distinguishes from siblings (nip_validate, regon_validate) by function and 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?
The description implies use for PESEL numbers, but provides no explicit guidance on when to use this tool versus the sibling tools for NIP or REGON. No when-not conditions or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
regon_validateAInspect
Validates the checksum of a 9- or 14-digit Polish business registry number (REGON). 9-digit: weights 8 9 2 3 4 5 6 7 over the first 8 digits, sum mod 11 (10 mapped to 0) must equal the 9th digit. 14-digit: the first 9 digits must themselves be a valid 9-digit REGON, and weights 2 4 8 5 0 9 7 3 6 1 2 4 8 over the first 13 digits (sum mod 11, 10 mapped to 0) must equal the 14th digit.
| Name | Required | Description | Default |
|---|---|---|---|
| value | Yes | digits-only identifier to validate (no spaces or dashes) |
Output Schema
| Name | Required | Description |
|---|---|---|
| valid | Yes | |
| reason | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It fully discloses the checksum algorithm for both 9- and 14-digit numbers, including weight sequences, modulo arithmetic, and how remainder 10 is handled. This is detailed, transparent, and gives the agent full understanding of the validation logic.
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—two sentences—and front-loads the core purpose before detailing the algorithm. It could be slightly more efficient by omitting the algorithm details or moving them elsewhere, but for a validation tool, including the algorithm is justified and 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?
Given that there is no output schema referenced (though context says 'Has output schema: true', no details are provided), the description adequately explains input validation logic. However, it does not mention what the output looks like (e.g., returns a boolean or error message), which would be helpful for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and there is only one parameter, already described as 'digits-only identifier to validate (no spaces or dashes)' in the schema. The description adds no extra semantic meaning beyond what the schema provides, so the baseline 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 that it validates the checksum of a Polish business registry number (REGON). It specifies the exact digit lengths (9 or 14), unlike siblings nip_validate or pesel_validate, making it well differentiated.
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 what the tool does but offers no guidance on when to use it versus nip_validate or pesel_validate. For example, it could mention that this is for business entities, while PESEL is for individuals and NIP is for tax identification, but it does not.
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.
3 tool updates
- First observed
nip_validate - First observed
pesel_validate - First observed
regon_validate
Frequently Asked Questions
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, then choose Claim with GitHub. An organization namespace such asio.github.acme/serveralso needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.HTTP challenge – works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon 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.
Discussions
No comments yet. Be the first to start the discussion!
Related MCP Connectors
Validates PESEL/NIP/REGON/IBAN/Luhn/ISBN/EAN/SWIFT-BIC/VAT; RPN calc, date math, hashing, tokens
Validates Luhn, IBAN, ISBN, EAN/UPC, SWIFT/BIC, and EU VAT checksums and formats.
Validate LatAm IDs: Mexican CLABE, Brazilian CNPJ/CPF checksums + BrasilAPI company/CEP/bank lookups
Polish company registry: 4.4M firms, KRS/REGON data, VAT white list checks, financial statements
Related MCP Servers
- AlicenseAqualityDmaintenanceEnables real-time verification of Polish NIP (Tax Identification Numbers) using the official Ministry of Finance API. Also supports checking if a bank account belongs to a specific NIP.220MIT
- AlicenseAqualityAmaintenanceProvides clean, typed access to the Polish REGON business register (GUS BIR1), enabling AI assistants to look up companies by NIP, REGON, or KRS and retrieve structured data like name, address, and legal form.61MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to verify Polish companies and EU VAT numbers against official government registries using 9 tools, with no API key and optional plain REST access.MIT
- AlicenseNot gradedqualityCmaintenanceProvides a Luhn check-digit validation tool for numeric strings such as credit cards, IMEI, and national IDs.9MIT