Paperless-ngx MCP Server for LlamaIndexGive LlamaIndex instant access to 26 tools to Create Correspondent, Create Document Type, Create Saved View, and more

Name: Paperless-ngx
Price: 29 USD
Availability: InStock
Rating: 4.9 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Paperless-ngx as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Ask AI about this MCP Server for LlamaIndex

Open in ChatGPT Open in Claude Open in Perplexity

The Paperless-ngx MCP Server for LlamaIndex is a standout in the Loved By Devs category — giving your AI agent 26 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

python

import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Paperless-ngx. "
            "You have 26 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Paperless-ngx?"
    )
    print(response)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Paperless-ngx MCP Server

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

LlamaIndex agents combine Paperless-ngx tool responses with indexed documents for comprehensive, grounded answers. Connect 26 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

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.

The Paperless-ngx MCP Server exposes 26 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 26 Paperless-ngx tools available for LlamaIndex

When LlamaIndex connects to Paperless-ngx through Vinkius, your AI agent gets direct access to every tool listed below — spanning digital-archive, ocr, full-text-search, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

create

Create correspondent on Paperless-ngx

Create a new correspondent

create

Create document type on Paperless-ngx

Create a new document type

create

Create saved view on Paperless-ngx

Create a new saved view

create

Create tag on Paperless-ngx

Create a new tag

delete

Delete correspondent on Paperless-ngx

Delete a correspondent

delete

Delete document on Paperless-ngx

Delete a document

delete

Delete document type on Paperless-ngx

Delete a document type

delete

Delete saved view on Paperless-ngx

Delete a saved view

delete

Delete tag on Paperless-ngx

Delete a tag

download

Download document on Paperless-ngx

Download the actual document file

get

Get correspondent on Paperless-ngx

Retrieve correspondent details

get

Get document on Paperless-ngx

Retrieve details of a specific document

get

Get document type on Paperless-ngx

Retrieve document type details

get

Get tag on Paperless-ngx

Retrieve tag details

list

List correspondents on Paperless-ngx

List all correspondents

list

List document types on Paperless-ngx

List all document types

list

List documents on Paperless-ngx

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

list

List saved views on Paperless-ngx

List all saved views

list

List tags on Paperless-ngx

List all tags

preview

Preview document on Paperless-ngx

Get a preview of the document

thumb

Thumb document on Paperless-ngx

Get the document thumbnail

update

Update correspondent on Paperless-ngx

Update a correspondent

update

Update document on Paperless-ngx

Update document metadata

update

Update document type on Paperless-ngx

Update a document type

update

Update tag on Paperless-ngx

Update a tag

upload

Upload document on Paperless-ngx

Upload a new document

Connect Paperless-ngx to LlamaIndex via MCP

Follow these steps to wire Paperless-ngx into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 26 tools from Paperless-ngx

Why Use LlamaIndex with the Paperless-ngx MCP Server

LlamaIndex provides unique advantages when paired with Paperless-ngx through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Paperless-ngx tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Paperless-ngx tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Paperless-ngx, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Paperless-ngx tools were called, what data was returned, and how it influenced the final answer

Paperless-ngx + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Paperless-ngx MCP Server delivers measurable value.

Hybrid search: combine Paperless-ngx real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Paperless-ngx to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Paperless-ngx for fresh data

Analytical workflows: chain Paperless-ngx queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for Paperless-ngx in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Paperless-ngx immediately.

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

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

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

Troubleshooting Paperless-ngx MCP Server with LlamaIndex

Common issues when connecting Paperless-ngx to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Paperless-ngx + LlamaIndex FAQ

Common questions about integrating Paperless-ngx MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Paperless-ngx tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.