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io.github.shibley/aidataparser
serveur MCP (Model Context Protocol) · aidataparser 1.0.0
Référencé dans l'annuaire. Seul le pentest comportemental fait foi, et il n'a pas encore été exécuté sur ce serveur.
Est-ce que io.github.shibley/aidataparser est sûr ?
Au dernier audit MCP Hub, le serveur MCP « io.github.shibley/aidataparser » est classé « Non encore testé ». Référencé dans l'annuaire. Seul le pentest comportemental fait foi, et il n'a pas encore été exécuté sur ce serveur. Le verdict est réévalué en continu ; consultez la fiche pour l'état à jour.
Méthode : MCP Hub analyse la description de chaque outil (couche 1) et, pour le verdict fort, exécute le serveur dans une micro-VM isolée avec leurres et réseau bloqué (couche 2). On publie des noms et des compteurs, jamais le contenu brut renvoyé par un outil.
Les 9 outils
- buy_credits≈ 251 tokens
Get a Stripe checkout link for a one-time credit pack, to hand to the user. Packs: `starter` $9 for 500 credits, `growth` $29 for 2,000 credits, `scale` $99 for 10,000 credits. Credits never expire; 1 credit per document. If this server has an API key set, the credits land on that key's account. Without a key, pass the user's `email` (ask them; do not invent one) — the page after payment shows their new API key. Creating the link charges nothing; the user pays on Stripe's page.
Paramètres, retour & exemple (2)
Paramètrespack· string · optionnel · starter | growth | scale
Which pack. Defaults to starter.email· string · optionnel
The user's email. Required only when no API key is set on this server; ignored when one is.
Exemple d'appel{"name": "buy_credits", "arguments": {"pack": "starter", "email": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - check_credits≈ 90 tokens
Return the number of extraction credits remaining on the authenticated API key. Free — does not consume a credit.
Paramètres, retour & exemple (0)
Exemple d'appel{"name": "check_credits", "arguments": {}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - create_api_key≈ 240 tokens
Start here if you do not have an AIDataParser API key. Provide the user's `email` and receive a live adp_live_ API key with 50 free credits — no card, no signup form. Configure it on this MCP server as `Authorization: Bearer <api_key>` to unlock parse_document, parse_text and infer_schema. The key is returned ONCE and is never shown again, so surface it to the user and store it. Ask the user for their address; do not invent one. Free — does not consume a credit.
Paramètres, retour & exemple (1)
Paramètresemail· string · requis
The user's email address. The account and its free credits belong to this address; an address that already has an account is refused rather than issued a second key.
Exemple d'appel{"name": "create_api_key", "arguments": {"email": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - infer_schema≈ 258 tokens
Given one sample document's `text`, propose a reusable JSON Schema for that document type. Use this when no built-in schema_id fits: infer a schema once, review it, then reuse it as `schema` on parse_document / parse_text across many documents for consistent output. Returns the JSON Schema plus a flat field list and an inferred doc_type. Costs 1 credit per successful call.
Paramètres, retour & exemple (3)
Paramètrestext· string · requis
A single representative sample of the document type, as text.doc_type· string · optionnel
Optional hint for what kind of document this is, e.g. "purchase order", "lab report".instructions· string · optionnel
Optional guidance on which fields matter or how to shape the schema.
Exemple d'appel{"name": "infer_schema", "arguments": {"text": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - list_schemas≈ 117 tokens
Return the built-in schema templates you can pass to parse_document as `schema_id` (invoice, receipt, resume, etc.), each with its id and the fields it extracts. Free — does not consume a credit and needs no API key.
Paramètres, retour & exemple (0)
Exemple d'appel{"name": "list_schemas", "arguments": {}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - parse_document≈ 402 tokens
Extract clean, schema-guaranteed JSON from a PDF or image. Provide the document via `url` or `base64`. Pass an optional JSON `schema` to constrain the output shape, and `instructions` to guide extraction. Returns the extracted data plus a confidence score and a review_needed flag. Costs 1 credit per successful call.
Paramètres, retour & exemple (7)
Paramètresurl· string · optionnel
Public http(s) URL of the PDF or image to parse.base64· string · optionnel
Base64-encoded document bytes (alternative to `url`). Provide `media_type` alongside it.redact· boolean · optionnel
When true, PII (emails, SSNs, card numbers, phones, etc.) is masked in the output before it leaves the server.schema· object · optionnel
Optional JSON Schema describing the exact output shape you want. When provided, the returned `data` conforms to it.schema_id· string · optionnel
Optional named template to use instead of a hand-written schema, e.g. "invoice", "receipt", "resume". Call the list_schemas tool for the full set. Ignored when `schema` is provided.media_type· string · optionnel
MIME type for `base64` input, e.g. application/pdf, image/png, image/jpeg.instructions· string · optionnel
Optional natural-language guidance for what to extract.
Exemple d'appel{"name": "parse_document", "arguments": {"url": "texte", "base64": "texte", "redact": true, "schema": {}, "schema_id": "texte", "media_type": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - parse_text≈ 375 tokens
Extract clean, schema-guaranteed JSON from raw/messy text you already have — scraped web content, email bodies, chat logs, OCR output, or pasted tables. Pass the text in `text`. Use this instead of parse_document when you don't have a file. Optional JSON `schema` (or `schema_id`) constrains the output shape and `instructions` guides extraction. Returns the extracted data plus a confidence score and a review_needed flag. Costs 1 credit per successful call.
Paramètres, retour & exemple (5)
Paramètrestext· string · requis
The raw text to extract structured data from.redact· boolean · optionnel
When true, PII (emails, SSNs, card numbers, phones, etc.) is masked in the output before it leaves the server.schema· object · optionnel
Optional JSON Schema describing the exact output shape you want. When provided, the returned `data` conforms to it.schema_id· string · optionnel
Optional named template to use instead of a hand-written schema, e.g. "invoice", "receipt", "resume". Call the list_schemas tool for the full set. Ignored when `schema` is provided.instructions· string · optionnel
Optional natural-language guidance for what to extract.
Exemple d'appel{"name": "parse_text", "arguments": {"text": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - try_parse≈ 375 tokens
Run a REAL extraction with no API key, no email and no signup, so you can see the output shape before committing to anything. Pass up to 4000 characters of messy text in `text` (an invoice, a receipt, a resume, scraped HTML, an email body) and optionally a `schema` or `schema_id` to constrain the result. Returns the same structured data, confidence and review_needed flag the paid tools return. Limited to 3 calls per caller per day — for real volume call create_api_key for 50 free credits, then use parse_text or parse_document.
Paramètres, retour & exemple (4)
Paramètrestext· string · requis
The raw text to extract structured data from, up to 4000 characters. Send a representative excerpt rather than a whole corpus.schema· object · optionnel
Optional JSON Schema describing the exact output shape you want. When provided, the returned `data` conforms to it.schema_id· string · optionnel
Optional named template to use instead of a hand-written schema, e.g. "invoice", "receipt", "resume". Call list_schemas for the full set. Ignored when `schema` is provided.instructions· string · optionnel
Optional natural-language guidance for what to extract.
Exemple d'appel{"name": "try_parse", "arguments": {"text": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - validate≈ 241 tokens
Check whether a JSON object conforms to a JSON `schema` (or a built-in `schema_id` template) and get back a valid flag plus per-field errors. Use this to verify data you already hold — a prior parse result, your own output, or an upstream feed — before acting on it or spending a credit. Deterministic, free, and needs no API key.
Paramètres, retour & exemple (3)
Paramètresdata· ? · requis
The JSON value to validate.schema· object · optionnel
JSON Schema to validate against. Takes precedence over schema_id.schema_id· string · optionnel
Built-in template id to validate against instead of a hand-written schema (invoice, receipt, resume, etc.). Call list_schemas for the full set.
Exemple d'appel{"name": "validate", "arguments": {"data": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]}
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