Skip to main content
Glama
Milli42

paperlessngx-mcp

by Milli42

paperless_search_documents

Read-only

Search and filter documents by query, correspondent, tag, or date range, returning only metadata—title, dates, tags, and page count—to reference without exposing full text.

Instructions

PRIVACY TIER 1 (metadata only): Search documents and return METADATA ONLY — never OCR content. Full-text search runs server-side inside Paperless; this tool returns only titles, dates, tags, correspondent and document-type names. Use this to find and reference documents without pulling their text into context. Returns id, title, correspondent_name, document_type_name, tags, created_date, added_date, page_count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
search_queryNoFull-text search across OCR content + title (matching happens on the server; content is NOT returned).
correspondent_nameNoFilter by correspondent name.
tagNoFilter by a single tag name.
document_typeNoFilter by document type name.
created_afterNoISO date YYYY-MM-DD (created on/after).
created_beforeNoISO date YYYY-MM-DD (created on/before).
inbox_onlyNoOnly documents currently in the inbox.
limitNoMax results (default 20).
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true. Description adds valuable context: privacy tier, server-side full-text search, and explicit statement that OCR content is never returned. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is single paragraph but well-structured and front-loaded with purpose. It contains all essential information without unnecessary words, though could be slightly more organized with bullet points.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 8 optional parameters, no output schema, and high schema coverage, the description sufficiently explains what the tool returns and how it operates. It mentions privacy and server-side search, which are important contextual details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description does not add parameter-specific semantics beyond the schema. It lists return fields but that does not compensate for parameter details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it searches documents and returns metadata only, with a specific list of returned fields. It distinguishes itself from siblings by emphasizing that it never returns OCR content, unlike paperless_get_document_content.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit guidance: 'Use this to find and reference documents without pulling their text into context.' This implies when to use and suggests not using when text is needed, but does not explicitly name alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Milli42/paperlessngx-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server