Validate, generate & convert EU e-invoices (UBL, CII, XRechnung, Factur-X) — EN 16931 pre-validated.
Convert an e-invoice between formats via the shared EN 16931 canonical model: parse the source document, re-serialize as the target, and validate the result before returning it — never a document that has not been checked. Format ids: "UBL_2.1" (OASIS UBL, the universal Peppol/EN16931 baseline), "UN_CEFACT_CII" (UN/CEFACT Cross Industry Invoice, required syntax for Chorus Pro/France and many ERP back-ends), "XRechnung_UBL" / "XRechnung_CII" (Germany's mandatory B2G format, XRechnung 3.0 — required for invoicing German public-sector buyers), "Factur-X" (France/Germany hybrid PDF+XML — a human-readable PDF/A-3 with the structured invoice embedded, common for French B2B). Binary formats (Factur-X) are base64 in both directions. Requires an API key on the Pro plan or above for any target beyond plain UBL_2.1 — call list_supported_formats to see current availability.
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | Target format id, e.g. "UN_CEFACT_CII", "XRechnung_UBL", "XRechnung_CII", or "Factur-X". | |
| from | Yes | Source format id, e.g. "UBL_2.1". | |
| document | Yes | The source document: raw text for XML formats, base64 for binary formats (Factur-X). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds behavioral context beyond annotations: validates before returning, handles binary formats with base64. No contradiction with annotations (readOnlyHint=false, idempotentHint=true).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is fairly long but front-loaded with core action. Each sentence earns its place, though some detail could be condensed. Well-structured with clear sections.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given complexity (multiple formats, binary, plan restrictions) and no output schema, the description is comprehensive—covers validation, base64, plan requirements, and sibling tool reference.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions. The description adds significant meaning to the parameters by detailing format IDs, binary handling, and source document format for 'from' parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts invoices between formats via a canonical model. It distinguishes from siblings like generate_invoice, validate_invoice, and list_supported_formats by focusing on conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on when to use (conversion between specific format IDs), including plan requirements and suggestion to call list_supported_formats for availability. Implicitly tells when not to use (e.g., if target requires higher plan).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Generate an EN 16931-conformant UBL 2.1 invoice from structured fields. The result is self-validated before being returned. Provide seller, buyer, and at least one line; for standard-rated (category "S") lines include a vatRate and the seller vatId.
| Name | Required | Description | Default |
|---|---|---|---|
| buyer | Yes | ||
| lines | Yes | ||
| seller | Yes | ||
| dueDate | No | ||
| payment | No | ||
| currency | Yes | ISO 4217, e.g. EUR. | |
| issueDate | Yes | ISO date, e.g. 2026-06-19. | |
| invoiceNumber | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses self-validation before return, which adds value beyond annotations. Annotations already indicate non-destructive and idempotent behavior, but no mention of authentication, rate limits, or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no redundancies. Front-loads key standard conformance and self-validation, then adds precise usage guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers essential aspects (standard, validation, critical parameters) but omits details on nested objects like seller, buyer, payment, dueDate. With no output schema, description could explain return value structure more.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is low (25%), but description adds critical meaning: mandates seller, buyer, lines, and specific conditions for vatRate and seller vatId on S-category lines. Partially compensates for missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it generates an EN 16931-conformant UBL 2.1 invoice. Distinguishes from siblings (convert, validate, list formats) by focusing on creation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit requirements: provide seller, buyer, at least one line, and for 'S' category lines include vatRate and seller vatId. Does not explicitly exclude alternatives but implies usage for generation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List the e-invoice formats InvoiceHub validates today and what is on the roadmap.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint. Description adds roadmap context, but no further behavioral traits are disclosed. Adequate given simplicity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single, front-loaded sentence with no redundant words. All information is essential.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters, no output schema, and simple read-only listing, the description fully covers the tool's functionality and roadmap aspect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist. Schema coverage is 100% (vacuous). Baseline of 4 applies as description need not add parameter info.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists supported e-invoice formats and roadmap. Verb 'list' and resource 'formats' are specific. It differentiates from siblings (convert, generate, validate) which are action-oriented.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance. However, the purpose is straightforward and sibling names imply their functions, so usage is implicitly clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Validate an EU e-invoice XML string against the official EN 16931 Schematron. Accepts either syntax — UBL 2.1 (Invoice or CreditNote) or UN/CEFACT CII — and auto-detects which. A document declaring the XRechnung 3.0 CustomizationID is additionally checked against KoSIT's XRechnung delta ruleset. Returns whether it is valid and any failing BR-* / BR-DE-* business rules.
| Name | Required | Description | Default |
|---|---|---|---|
| xml | Yes | Raw e-invoice XML (UBL 2.1 or UN/CEFACT CII). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds significant behavioral context beyond this: it specifies the validation standard, the auto-detection of UBL vs CII, the additional XRechnung 3.0 check, and the return of failing BR-*/BR-DE-* rules. This fully compensates for the absence of an output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, each adding essential information: the core validation, the accepted syntaxes and auto-detection, and the special XRechnung handling and output. No redundant or filler content exists; it is front-loaded with the main verb and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (one parameter, no output schema), the description is complete. It covers the input format, validation rules, edge case (XRechnung), and return value (validity + failing rules). It also distinguishes itself from sibling tools through its focus on validation, making it sufficient for an agent to select and invoke confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers the single parameter 'xml' with a description of accepted formats, giving 100% coverage. The description enhances this by clarifying that both UBL and CII are accepted and auto-detected, and it introduces the XRechnung CustomizationID nuance that affects validation. This adds meaning beyond the schema, so it earns above the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the primary action (validate) against a specific standard (EN 16931 Schematron) and enumerates accepted input formats (UBL 2.1, CII). It distinguishes itself from sibling tools like convert_invoice and generate_invoice by focusing on validation, not conversion or generation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: 'Validate an EU e-invoice XML string against the official EN 16931 Schematron' and explains the auto-detection of syntax. However, it does not explicitly contrast with alternatives (e.g., when to use convert_invoice instead) or provide when-not-to-use guidance, so it misses the explicit exclusion needed for a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
validate_invoice1 field changedInput schema / properties / xml / descriptionPrevious value: -"Raw UBL 2.1 invoice XML."New value: +"Raw e-invoice XML (UBL 2.1 or UN/CEFACT CII)."convert_invoicegenerate_invoicelist_supported_formatsvalidate_invoiceClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
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Create, validate, convert & extract compliant e-invoices (UBL, Factur-X, ZUGFeRD, XRechnung)
Generate & validate EN 16931 e-invoices (Factur-X, ZUGFeRD, XRechnung); verification certificates
EN 16931: validate invoice data or a UBL/CII file, emit UBL or CII XML. XRechnung, Peppol. Not PDF.
Generate, validate and read Factur-X / EN 16931 e-invoices (France, EU): PDF/A-3, CII, UBL 2.1.
Add one secure layer between your agents and this server.
Each tool addresses a distinct operation—generate creates, validate checks, convert transforms, and list_supported_formats provides metadata—with no functional overlap. The descriptions make the boundaries between tools crystal clear.
All tool names follow a consistent verb_noun pattern (convert_invoice, generate_invoice, list_supported_formats, validate_invoice), with the object being the domain concept. This makes the set predictable and easy to navigate.
With only 4 tools, the server is tightly scoped to e-invoice processing—each tool earns its place, and the count is neither too thin nor bloated. It is an ideal size for the utility's purpose.
The set covers the core workflow: generating invoices, validating them, converting between formats, and discovering supported formats. There are no obvious gaps for the stated domain; users can perform all essential operations.
