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Rechnungslotse: deutsche E-Rechnung

E-Rechnung im Klartext lesen

rechnung_lesen
Read-only

Liest den Datensatz einer XRechnung oder eines ZUGFeRD-PDF und gibt Absender, Empfänger, Positionen, Beträge, Fälligkeit und Bankverbindung strukturiert zurück – ohne die Datei zu speichern.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
xmlNoDer XML-Inhalt der E-Rechnung als Text (XRechnung/UBL oder CII). Entweder dieses Feld ODER datei_base64.
dateinameNoDateiname mit Endung (.xml oder .pdf) – daraus wird der Typ bestimmt. Vorgabe: rechnung.xml
datei_base64NoDie Datei Base64-kodiert – nötig für ZUGFeRD-PDF, geht auch für XML.

Schema Changelog

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

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

The annotation readOnlyHint is consistent with the description's claim of not saving the file. The description also specifies that it returns structured data, providing full transparency about the read-only behavior without any side effects.

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 is concise and to the point. It avoids unnecessary details while covering the main functionality and output, making it easy for an agent to parse.

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?

Given the tool's moderate complexity (three optional parameters) and lack of an output schema, the description is complete. It lists the key return fields, which is essential for the agent to understand what data will be provided, and it clarifies the file type handling (XRechnung vs. ZUGFeRD-PDF).

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 input schema provides 100% coverage with descriptive comments for each parameter, including the mutual exclusivity of xml and datei_base64. However, the tool description itself does not add further meaning to the parameters beyond what the schema already provides, so the baseline score of 3 applies.

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 clearly states the action (reads) and the resource (XRechnung or ZUGFeRD-PDF), and lists the specific data returned (sender, recipient, positions, amounts, due date, bank details). It distinguishes itself from sibling tools that create, check, or search invoices.

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?

The description explains what the tool does but does not explicitly name alternative tools or conditions for choosing this one. It mentions 'ohne die Datei zu speichern' which hints at a read-only operation, but it lacks direct guidance on when to prefer this over rechnung_pruefen or rechnung_erstellen.

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

A3.9/5.0
Disambiguation4/5

Most tools target distinct resources (customers, services, invoices, payments, legal checks), but rechnung_erstellen vs. leistungen_abrechnen both create invoices and rechnung_pruefen vs. pflichtangaben_pruefen both validate invoices, though with different inputs and scopes. The descriptions are detailed enough to resolve ambiguity after careful reading.

Naming Consistency3/5

The dominant pattern is object_verb (kunden_suchen, rechnung_erstellen, zahlung_erfassen), but several names are noun phrases (offene_posten, leistungen_offen, umsatzsteuer_aufstellung) or noun_noun (rechnung_datei). This mixed convention is still readable but lacks a uniform verb-based structure.

Tool Count3/5

At 18 tools, the server sits in the borderline-heavy range (16-25). The domain of German e-invoicing is broad, but the large number is not fully justified by tool specialization, as some functions (e.g., multiple validation tools) could be consolidated.

Completeness3/5

The surface covers the core lifecycle of services, invoicing, payment recording, and validation, but notable operations are missing: creating credit notes (explicitly referenced in zahlung_erfassen), managing customers, and updating/cancelling invoices. These gaps can lead to dead ends in common workflows like handling overpayments or customer changes.

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