InvoiceIn

Export invoice as DATEV Buchungsstapel

invoice_to_datev

Read-onlyIdempotent

DATEV Buchungsstapel (EXTF 700) text for the incoming invoice: one booking row per VAT-rate group, automatic expense accounts by SKR. Verify account mapping with the tax advisor before import.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`skr`	No	German chart of accounts: '03' (SKR03) or '04' (SKR04)	03
`path`	No	Local file path instead of file_base64; only honoured when the server runs over stdio on the same machine.
`file_base64`	No	The invoice file, base64-encoded: XML (UBL, CII, XRechnung, Peppol, FatturaPA, KSeF FA(3)) or a ZUGFeRD/Factur-X hybrid PDF. Up to 25 MB decoded.
`creditor_account`	No	Creditor (Gegenkonto) number to post the invoice against, e.g. 70000	70000

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedSep 7, 2026

TDQS

A4.2/5.0

Behavior4/5

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

The description adds behavioral detail beyond the annotations: output is EXTF 700 text, booking rows are grouped by VAT-rate group, and expense accounts are automatically derived using SKR. The caveat to verify account mapping with the tax advisor is also useful operational context. No contradiction with the read-only and idempotent hints.

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?

Two sentences with no filler: the first sentence front-loads the output format and key behavioral detail, and the second adds the necessary tax-advisor caution. It is appropriately sized for the tool's complexity.

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?

Given the rich schema, output schema, and annotations, the description covers what the tool produces and the important import caveat. It does not explicitly say that one of file_base64 or path must be supplied, but the schema already documents those alternatives and constraints.

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?

The schema already documents all four parameters with 100% coverage, including formats, defaults, and constraints. The description adds that SKR drives automatic expense-account selection, but it does not provide significant new parameter-level meaning beyond the schema.

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 states a specific verb and resource: Export invoice as DATEV Buchungsstapel (EXTF 700) text. It also explains what is produced, 'one booking row per VAT-rate group', which clearly distinguishes it from sibling tools like invoice_to_csv and invoice_to_html.

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 intended context is clear: this is for converting an incoming invoice into DATEV import format, with a warning to verify account mapping with a tax advisor before import. It does not explicitly name alternatives or state when not to use it, but the DATEV-specific language makes the use case unambiguous.

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

All InvoiceIn tools Inspect

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TDQS

A3.9/5.0

Disambiguation4/5

The three conversion tools are clearly separated by output format, and the parse versus validation distinction is mostly clear. The main overlap is between read_invoice and validate_invoice since both produce validation reports, though the descriptions clarify that read_invoice returns the full canonical invoice while validate_invoice is a cheaper validation-only operation.

Naming Consistency4/5

The conversion tools follow a consistent invoice_to_<format> pattern, while read_invoice and validate_invoice use a verb_invoice pattern. This is readable and predictable, but slightly inconsistent because the conversions do not follow the same verb-first style.

Tool Count5/5

Five tools is well-scoped for an invoice processing server: parsing, validation, and three common output conversions. Each tool has a distinct role, and the count does not feel padded or thin.

Completeness4/5

The server covers the core invoice workflow: read, validate, and convert to useful outputs. Minor gaps exist, such as no explicit listing of supported source formats or batch/multiple invoice handling, but these are not critical for the apparent purpose.

Resources

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