
Paperless-NGX
STDIO管理无纸化NGX文档、标签、通信方和文档类型的MCP服务器
管理无纸化NGX文档、标签、通信方和文档类型的MCP服务器
An MCP (Model Context Protocol) server for interacting with a Paperless-NGX API server. This server provides tools for managing documents, tags, correspondents, and document types in your Paperless-NGX instance.
To install Paperless NGX MCP Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @baruchiro/paperless-mcp --client claude
Add these to your MCP config file:
// STDIO mode (recommended for local or CLI use)
"paperless": { "command": "npx", "args": [ "-y", "@baruchiro/paperless-mcp@latest", ], "env": { "PAPERLESS_URL": "http://your-paperless-instance:8000", "PAPERLESS_API_KEY": "your-api-token" } }
// HTTP mode (recommended for Docker or remote use)
"paperless": { "command": "docker", "args": [ "run", "-i", "--rm", "ghcr.io/baruchiro/paperless-mcp:latest", ], "env": { "PAPERLESS_URL": "http://your-paperless-instance:8000", "PAPERLESS_API_KEY": "your-api-token" } }
Get your API token:
Replace the placeholders in your MCP config:
http://your-paperless-instance:8000
with your Paperless-NGX URLyour-api-token
with the token you just generatedThat's it! Now you can ask Claude to help you manage your Paperless-NGX documents.
Here are some things you can ask Claude to do:
Get a paginated list of all documents.
Parameters:
list_documents({ page: 1, page_size: 25 })
Get a specific document by ID.
Parameters:
get_document({ id: 123 })
Full-text search across documents.
Parameters:
search_documents({ query: "invoice 2024" })
Download a document file by ID.
Parameters:
download_document({ id: 123, original: false })
Perform bulk operations on multiple documents.
Parameters:
Examples:
// Add a tag to multiple documents bulk_edit_documents({ documents: [1, 2, 3], method: "add_tag", tag: 5 }) // Set correspondent and document type bulk_edit_documents({ documents: [4, 5], method: "set_correspondent", correspondent: 2 }) // Merge documents bulk_edit_documents({ documents: [6, 7, 8], method: "merge", metadata_document_id: 6, delete_originals: true }) // Split document into parts bulk_edit_documents({ documents: [9], method: "split", pages: "[1-2,3-4,5]" }) // Modify multiple tags at once bulk_edit_documents({ documents: [10, 11], method: "modify_tags", add_tags: [1, 2], remove_tags: [3, 4] })
Upload a new document to Paperless-NGX.
Parameters:
post_document({ file: "base64_encoded_content", filename: "invoice.pdf", title: "January Invoice", created: "2024-01-19", correspondent: 1, document_type: 2, tags: [1, 3], archive_serial_number: "2024-001" })
Get all tags.
list_tags()
Create a new tag.
Parameters:
create_tag({ name: "Invoice", color: "#ff0000", match: "invoice", matching_algorithm: "fuzzy" })
Get all correspondents.
list_correspondents()
Create a new correspondent.
Parameters:
create_correspondent({ name: "ACME Corp", match: "ACME", matching_algorithm: "fuzzy" })
Get all document types.
list_document_types()
Create a new document type.
Parameters:
create_document_type({ name: "Invoice", match: "invoice total amount due", matching_algorithm: "any" })
The server will show clear error messages if:
Want to contribute or modify the server? Here's what you need to know:
npm install
node server.js http://localhost:8000 your-test-token
The server is built with:
This MCP server implements endpoints from the Paperless-NGX REST API. For more details about the underlying API, see the official documentation.
The MCP server can be run in two modes:
This is the default mode. The server communicates over stdio, suitable for CLI and direct integrations.
npm run start -- <baseUrl> <token>
To run the server as an HTTP service, use the --http
flag. You can also specify the port with --port
(default: 3000). This mode requires Express to be installed (it is included as a dependency).
npm run start -- <baseUrl> <token> --http --port 3000
POST /mcp
on the specified port./mcp
will return 405 Method Not Allowed.This project is a fork of nloui/paperless-mcp. Many thanks to the original author for their work. Contributions and improvements may be returned upstream.