# mcp-paperless-ngx

> mcp-paperless-ngx — code-omega-solutions-mcp-paperless-ngx. Use this tool when you need to manage documents and workflows efficiently, as it provides a read-only and write server for Paperless-ngx, enabling document organization and automation through natural language inputs. It solves problems related to document clutter and disorganization by allowing users to create tags, correspondents, and document types, and set up sorting workflows. It takes natural language inputs and outputs organized document metadata and workflows.

Canonical page: https://skillsregistry.net/skills/code-omega-solutions-mcp-paperless-ngx  
JSON: https://api.skillsregistry.net/v1/skills/code-omega-solutions-mcp-paperless-ngx

## Description

A read-only and write MCP server for Paperless-ngx, enabling document listing, metadata retrieval, and creation of tags, correspondents, document types, and sorting workflows via natural language.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/tvnpdsxa33)
- **Repository:** <https://github.com/Code-Omega-Solutions/mcp-paperless-ngx>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "code-omega-solutions-mcp-paperless-ngx"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/code-omega-solutions-mcp-paperless-ngx` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/code-omega-solutions-mcp-paperless-ngx/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt