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GSTIN check (India)

gstin_check
Read-onlyIdempotent

Validate an Indian GSTIN by structure (2-digit state code + PAN + entity code + 'Z') and its mod-36 cross-sum checksum.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gstinYes15-character Indian Goods and Services Tax Identification Number.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolNo
scopeNo
validYes
reasonYes
countryNo
normalizedNo

TDQS

A4.6/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With annotations already declaring readOnlyHint, idempotentHint, and openWorldHint=false, the description adds specific behavioral context by explaining the exact validation algorithm (structural pattern and mod-36 cross-sum checksum). It does not contradict annotations and provides the key behavioral detail that this is a rule-based syntax check.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that leads with the action and resource, then packs the validation criteria into a compact parenthetical. No unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple, with one well-documented parameter, a complete schema description, and an output schema present. The description provides the validation logic, and annotations cover safety and idempotency, so everything an agent needs to invoke and interpret the tool correctly is present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although the schema already describes the gstin parameter as a 15-character Indian GSTIN, the description goes beyond by breaking down the internal format and mentioning the checksum. This helps the agent construct or understand valid input values, adding real semantic value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Validate' and identifies the resource as 'Indian GSTIN', then distinguishes it from sibling validation tools by detailing the exact structure (2-digit state code + PAN + entity code + 'Z') and mod-36 checksum. This makes the tool's purpose unambiguous and clearly differentiates it from other checks in the sibling list.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies the tool is for validating Indian GSTINs, so an agent knows when to use it. However, it does not explicitly state when not to use it or mention alternatives such as vat_mod97_check or luhn_check, so it stops short of full routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.8/5.0
Disambiguation5/5

Each tool targets a distinct identifier type or data source: every checksum validation is for a specific standard (IBAN, LEI, VAT, etc.), and the on-chain and rental tools are clearly separate domains. There is no ambiguity between tools; even similar-sounding checks like 'luhn_check' and 'ean13_check' are distinct algorithms with explicit descriptions.

Naming Consistency3/5

Most validation tools follow a 'X_check' pattern (iban_check, swift_bic_check, ein_format_check), but others deviate: 'company_number_format' uses a noun_noun structure, 'block_info' is noun_noun, and 'batch_validate' and 'context_distill' use verbs. While the pattern is not uniform, the names are readable and the convention is understandable, just not fully consistent.

Tool Count2/5

With 28 tools, this server exceeds the typical 3-15 well-scoped range and even the 16-25 heavy range. The server covers multiple unrelated domains (identifier validation, blockchain queries, rental fraud, text processing), which inflates the count. While each tool is individually justified, the overall surface feels overly broad for a single MCP server.

Completeness4/5

For each sub-domain, coverage is strong: identifier validation includes a wide range of international standards, on-chain queries cover balances, activity, and settlement history, and rental tools provide risk, verdict, and deposit guard. Minor gaps exist (e.g., no country-specific tax IDs beyond what's listed, no transaction history for arbitrary tokens), but the visible coverage is comprehensive for the stated purposes.

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