InvoiceIn

Validate invoice

validate_invoice

Read-onlyIdempotent

Validation only: which rule sets were applied (XSD, EN 16931, XRechnung, Peppol, arithmetic), the errors and warnings with fix hints, and the invoice header. Cheaper to read than read_invoice when you only need a verdict.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`lang`	No	Language of the fix hints and rendering labels: en, de, pl, it or fr.	en
`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.

Output Schema

TableJSON Schema

Name	Required	Description
`ok`	Yes
`error`	No
`source`	No
`document`	No	Invoice header: id, issue_date, currency, due_date …
`validation`	No

Schema Changelog

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

First observedSep 7, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds meaningful beyond-annotation context: validation returns only rule sets and diagnostics (not full data), and it is cheaper to read than read_invoice. No contradiction with annotations.

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. 'Validation only' is front-loaded, the output expectations are compactly listed, and the sibling comparison is a single clause. Every part earns its place.

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 output schema exists, all parameters are self-documented, and annotations cover safety/idempotence, the description is complete for a validation tool. It states the purpose, outputs, and the key alternative without missing critical invocation context.

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 description coverage is 100%, with each of the three optional parameters already documented in detail (lang pattern, path limitation, file_base64 formats and 25 MB cap). The description adds no parameter-specific semantics, so the baseline 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 uses a specific verb and resource ('validate invoice') and immediately scopes the tool with 'Validation only'. It enumerates the exact output categories: applied rule sets, errors/warnings with fix hints, and invoice header, which clearly distinguishes it from siblings like read_invoice.

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 explicitly names read_invoice as the main alternative and gives a clear selection criterion: 'when you only need a verdict' and 'Cheaper to read'. It stops short of stating the full when-not case, but the guidance is specific and actionable.

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

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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

Need Help?