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zatca-mcp

zatca-mcp

by DoubleH10
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

decode_qr

Decode ZATCA TLV-encoded QR codes from invoices. Extracts all embedded tag values into a readable JSON format for verification and inspection.

Instructions

Decode a ZATCA TLV-encoded QR code string.

Useful for verifying or inspecting existing QR codes from ZATCA-compliant invoices. Extracts all encoded tag values.

Args: qr_base64: Base64-encoded TLV string from a ZATCA QR code

Returns: JSON with decoded tag names and their values

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "qr_base64": "<qr_base64>"
    },
    "name": "decode_qr"
  }
}

Input Schema

NameRequiredDescriptionDefault
qr_base64Yes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

No annotations provided, but description fully discloses behavior: extracts all encoded tag values and returns JSON. No side effects implied; adequate for a read-only decode operation.

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?

Concise, front-loaded with purpose, uses clear labeled sections for args and returns. 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?

Complete for a single-parameter decode tool with output schema; covers input format, output format, and usage context. No missing information.

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

Parameters4/5

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

Schema coverage is 0%, but description fully explains the parameter: 'Base64-encoded TLV string from a ZATCA QR code', adding meaning beyond the schema's type.

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?

Description clearly states 'Decode a ZATCA TLV-encoded QR code string' with verb and resource; distinguishes from sibling generate_qr_code by specifying decoding vs generating.

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?

Explicitly says 'useful for verifying or inspecting existing QR codes from ZATCA-compliant invoices' providing context; could be improved by explicitly contrasting with validate_invoice but overall clear.

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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