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Doxis AI.dp (Klippa DocHorizon) MCP by usefulapi

Convert an e-invoice to Universal Invoice JSON

dochorizon_convert_einvoice

Convert an e-invoice (XML or hybrid PDF) to the Universal Invoice JSON structure (parties, lines, taxes, totals). Nothing is sent to anyone. May use credits per your pricing. POST /einvoicing/v1/tools/convert/einvoice.

Input Schema

NameRequiredDescriptionDefault
xmlNoThe e-invoice as XML text (UBL, CII, ...).
validateNoValidate the e-invoice during conversion.
data_base64NoThe e-invoice file as base64 (XML, or a hybrid PDF such as ZUGFeRD / Factur-X).
einvoice_typeNoThe e-invoice type, if it should not be auto-detected (see dochorizon_list_einvoice_types).
include_unmapped_fieldsNoAlso return fields of the original that have no place in the universal format.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint=false, destructiveHint=false, openWorldHint=true, idempotentHint=false). The description adds genuinely useful context beyond them: no data is transmitted externally, and credit consumption may apply. It could go further (e.g. what 'readOnlyHint=false' concretely means here), but it earns credit for the added behavioral detail.

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

Conciseness4/5

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

Front-loads the purpose in the first sentence and follows with three short, useful statements. Efficient overall, though the raw POST endpoint adds little value for an agent choosing a tool.

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

Completeness4/5

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

No output schema exists, so the description carries the burden of describing the return value; it names the Universal Invoice JSON structure and its main sections, which is reasonably sufficient. Parameter semantics are fully covered by the schema, so coverage is adequate.

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

Parameters3/5

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

Schema coverage is 100%, so all five parameters (xml, data_base64, validate, einvoice_type, include_unmapped_fields) are already fully documented in the schema. The description adds no syntax or format guidance beyond that, so baseline 3 is correct.

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?

States a specific verb (Convert) and resource (an e-invoice in XML or hybrid PDF) plus the target format (Universal Invoice JSON, with parties/lines/taxes/totals). This clearly distinguishes it from siblings like dochorizon_validate_einvoice and dochorizon_capture_einvoice.

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

Usage Guidelines3/5

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

Usage is only implied: the standard path is to feed an existing e-invoice XML/PDF and get JSON back. It never states when to prefer this over validate_einvoice or capture_einvoice, nor any prerequisites (e.g. credit requirements, auth). Adequate but leaves the agent to infer.

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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