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Doxis AI.dp (Klippa DocHorizon) MCP by usefulapi

Capture an invoice or receipt

dochorizon_capture_financial

SPENDS CREDITS: extract structured data from an invoice, receipt or other financial document with the Financial model: merchant and customer, dates, totals, VAT, line items, payment details, currency, and more (as the chosen configuration enables). Uses your own Doxis AI.dp (Klippa) credits: billed per request or per page depending on the service (extra components in a configuration can add cost), at your project's price (Billing → Pricing in the platform); a new account starts with EUR 25 of free credit. Give the document as exactly one of url (public https), data_base64 (small files) or file_id (a stored file). Synchronous; for long documents use dochorizon_submit_async_capture. POST /document_capturing/v1/financial.

Input Schema

NameRequiredDescriptionDefault
urlNoPublic https URL of the document. Klippa downloads it (must complete within 30 seconds).
file_idNoA Doxis AI.dp storage file id (from dochorizon_upload_file or a toolkit result).
filenameNoA name for the file (helps content-type detection).
passwordNoPassword of a protected PDF. Only used for this request.
data_base64NoThe document as base64 (at most about 1.5 MB of file). Prefer url or file_id for anything bigger.
page_rangesNoPages to process, for example '1-3, 5', '2-last', 'first-last' (default: all pages; documents over 50 pages time out).
content_typeNoMIME type, if it cannot be detected.
configuration_slugNoSlug of a capturing configuration made in the platform (see dochorizon_list_configurations). Optional: the model's defaults apply without it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
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, idempotentHint=false). The description adds genuinely non-structured context: credit spend, per-request vs per-page billing, and the EUR 25 free-credit detail. It does not disclose the return format, but the billing/cost disclosure is meaningful added value.

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 most decision-relevant fact ('SPENDS CREDITS') then the capability, input rule, and sync guidance. The billing sentence is dense with parenthetical detail, but each sentence serves a distinct purpose.

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 no output schema, the description should ideally hint at the return shape; it lists the extracted fields (merchant, totals, VAT, line items, currency) which partly covers this. Billing, sync behavior, and input constraints are all present, so the agent has enough to call it correctly.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds a real constraint beyond the schema — 'exactly one of url, data_base64 or file_id' — clarifying the mutually exclusive input methods, which the schema does not express.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('extract structured data from an invoice, receipt or other financial document') and names the Financial model, so the agent knows what it produces. Sibling differentiation is only partial: 'other financial document' is broad and overlaps with dochorizon_capture_bank_statement and dochorizon_capture_einvoice without explicitly excluding them.

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?

Explicitly states the sync/async split and routes long documents to dochorizon_submit_async_capture. Does not state when to prefer this Financial capture over the einvoice/generic siblings, but the model framing implies it.

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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