mindee

Turn PDFs and images into typed fields — invoices, receipts, IDs and custom models — via Mindee OCR.

Sollte ich dies verwenden

Qualität und Sicherheit

A
Qualität der Beschreibung
100%
Vollständigkeit des Schemas
98%
Qualität der Benennung
100%
Risiko der Vergiftung
100%
Übereinstimmung der Berechtigungen
100%
Einhaltung des Protokolls
100%

Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.

Kontextkosten

~878Tokens (Tool-Definitionen)
~1.5 KBTypische Antwortgröße
Mittlere Auswirkung auf die Aufmerksamkeit (0.69% von 128k Kontext)

Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.

Installieren

Installation mit einem Klick

Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:

{
  "mcpServers": {
    "mindee": {
      "url": "https://mindee.usefulapi.io/mcp"
    }
  }
}

Remote-Endpunkte

https://mindee.usefulapi.io/mcpstreamable-http

Was es kann

Tool-Inventar

Tools (4)

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🟢mindee_list_models(name, model_type)

List the document-extraction models available to your Mindee account (id, name, type). Use a model's `id` as the model_id for mindee_extract_document. V2 API: GET /v2/search/models.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "name": {
      "description": "Optional case-insensitive name filter, e.g. 'invoice'.",
      "type": "string"
    },
    "model_type": {
      "description": "Optional model type filter.",
      "type": "string"
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢mindee_get_job(job_id)

Check the processing status of an enqueued document by job id. Status is Waiting | Processing | Processed | Failed. When Processed, the response carries a result_url; pass that inference id to mindee_get_inference. V2 API: GET /v2/jobs/{job_id}.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "job_id": {
      "type": "string",
      "description": "Job id returned by mindee_extract_document (when it times out) or an enqueue call."
    }
  },
  "required": [
    "job_id"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢mindee_get_inference(inference_id, raw)

Fetch the structured result of a completed inference by id, returned as a compact map of extracted fields (plus raw_text if it was requested). V2 API: GET /v2/inferences/{inference_id}.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "inference_id": {
      "type": "string",
      "description": "Inference id (from a Processed job's result_url, or from mindee_extract_document)."
    },
    "raw": {
      "description": "Return the full unshaped API response instead of the compact fields map. Default false.",
      "type": "boolean"
    }
  },
  "required": [
    "inference_id"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟡mindee_extract_document(model_id, document_url, file_base64, filename, alias, ...)

Submit a document (PDF or image) to a Mindee extraction model and return the structured fields. Provide EITHER document_url (a public URL) OR file_base64 (+ filename). This enqueues an inference and polls until it completes (up to ~30s); if it is still processing it returns a job_id you can poll with mindee_get_job then read with mindee_get_inference. NOTE: consumes Mindee API credits (paid, billed per page). V2 API: POST /v2/inferences/enqueue.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "model_id": {
      "type": "string",
      "description": "Extraction model id (from mindee_list_models)."
    },
    "document_url": {
      "description": "Public URL of the document to process. Use this OR file_base64.",
      "type": "string",
      "format": "uri"
    },
    "file_base64": {
      "description": "Base64-encoded document bytes. Use this OR document_url; set `filename` too.",
      "type": "string"
    },
    "filename": {
      "description": "Filename for file_base64 uploads, e.g. 'invoice.pdf'.",
      "type": "string"
    },
    "alias": {
      "description": "Your own reference tag echoed back in the job/result.",
      "type": "string"
    },
    "webhook_ids": {
      "description": "Webhook ids to notify on completion (async flows).",
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "rag": {
      "description": "Enable Retrieval-Augmented Generation for the model, if configured.",
      "type": "boolean"
    },
    "raw_text": {
      "description": "Also return the full OCR raw text of the document.",
      "type": "boolean"
    },
    "polygon": {
      "description": "Return bounding-box polygons for fields.",
      "type": "boolean"
    },
    "confidence": {
      "description": "Return per-field confidence levels (Certain/High/Medium/Low).",
      "type": "boolean"
    }
  },
  "required": [
    "model_id"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

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