MCP For Claude Marketplace
Paperless-ngx

Paperless-ngx MCP Connector for Claude

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Manage your digital archive via Paperless-ngx — search documents, upload files, manage tags, and organize correspondents directly from any AI agent.

26 tools Official Updated Jun 28, 2026 Official Vinkius Partner
More Details Connect to Claude

Connect your Paperless-ngx instance to any AI agent and transform your document archive into a searchable, conversational knowledge base.

What you can do

  • Document Discovery — Use list_documents with full-text search or filter by tags and dates to find exactly what you need in seconds.
  • File Operations — Upload new documents with upload_document, download originals with download_document, or get instant visual context with preview_document and thumb_document.
  • Metadata Management — Organize your library by creating and updating tags, correspondents, and document types using dedicated tools like create_tag or update_correspondent.
  • Deep Inspection — Fetch complete OCR text and metadata for any specific file using get_document to help your AI analyze contents.
  • Saved Views — Access your predefined filters and organizational structures with list_saved_views.

How it works

  1. Subscribe to this server
  2. Provide your Paperless-ngx API URL and Personal API Token
  3. Start chatting with your documents in Claude, Cursor, or any MCP-compatible client

No more manual searching through folders. Your AI acts as a digital librarian that knows every word in your archive.

Who is this for?

  • Home Office Users — instantly find utility bills, tax records, or manuals without digging through physical or digital piles.
  • Legal & Admin Teams — query specific correspondents or document types to build reports or verify information quickly.
  • Researchers — manage large collections of PDFs and papers with automated tagging and content retrieval.
digital-archiveocrfull-text-searchfile-managementdocument-indexingopen-source

26 tools expose this connector's capabilities to your AI agent.

list_tags

List all tags

delete_tag

Delete a tag

download_document

Download the actual document file

get_correspondent

Retrieve correspondent details

get_document

Retrieve details of a specific document

get_document_type

Retrieve document type details

get_tag

Retrieve tag details

list_correspondents

List all correspondents

list_document_types

List all document types

list_documents

Supports filtering and searching via query parameters. List all documents in Paperless-ngx

preview_document

Get a preview of the document

thumb_document

Get the document thumbnail

update_correspondent

Update a correspondent

update_document

Update document metadata

update_document_type

Update a document type

update_tag

Update a tag

upload_document

Upload a new document

create_tag

Create a new tag

create_correspondent

Create a new correspondent

create_document_type

Create a new document type

create_saved_view

Create a new saved view

list_saved_views

List all saved views

delete_correspondent

Delete a correspondent

delete_document

Delete a document

delete_document_type

Delete a document type

delete_saved_view

Delete a saved view

See how to talk to your AI agent using Paperless-ngx.

Search for all documents related to 'Electricity Bill' from 2023.

I've searched your archive using `list_documents`. I found 3 documents: 'Jan 2023 Electricity' (ID: 101), 'Feb 2023 Electricity' (ID: 105), and 'March 2023 Electricity' (ID: 110). Would you like to see the details of one of them?

Upload a new document titled 'Contract 2024' with tag ID 12.

Processing the upload... I've successfully used `upload_document` to add 'Contract 2024'. It has been assigned ID 250 and is now being processed by Paperless-ngx for OCR.

Get the full content and a preview of document ID 42.

I've retrieved the data for document 42 using `get_document` and `preview_document`. The document is a 'Lease Agreement'. The OCR text mentions a monthly rent of $1,200. I've also generated a preview link for you.

Yes. The `list_documents` tool allows you to filter by `tags__id__in` and `created__date__gte`. You can also perform a full-text search using the `query` parameter.

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