Skip to main content
Glama
chrisguidry

paperless-mcp

by chrisguidry

List custom fields

list_custom_fields
Read-only

List custom fields defined in a paperless-ngx archive, optionally filtered by IDs or name, to find field IDs used for document values and search queries.

Instructions

List the custom fields defined in the archive.

get_document returns a document's custom field values by field ID. A select field's value is the id of one of the field's select_options. Search custom field values with search_documents, using a query like "custom_fields.value:overdue".

Input Schema

NameRequiredDescriptionDefault
idsNoReturn only the custom fields with these IDs (default: none)
pageNoPage number, starting at 1 (default: 1)
page_sizeNoNumber of custom fields per page (default: 100)
name_containsNoCase-insensitive substring of the name (default: none)

Output Schema

NameRequiredDescriptionDefault
paginationYesThe position of one page of results in the full result set.
custom_fieldsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuine domain context beyond that: select fields carry select_options and their values are option IDs, which an agent needs to interpret results. It omits pagination/ordering behavior, but that is largely schema-covered, so a 4 is fair.

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?

Purpose is front-loaded in the first sentence, followed by tightly related data-model and search guidance. Slightly sprawling across three topics with line breaks in odd places, but every sentence carries information.

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?

With an output schema present, return values needn't be explained, and the description fills the remaining gaps: what a custom field value looks like and how to search by it. Minor omission of result ordering/limits keeps it from a 5.

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 description coverage is 100%, with ids, name_contains, page, and page_size all documented inline including defaults. The description adds nothing about parameter syntax or interactions, so the schema carries it and the baseline 3 applies.

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

Purpose4/5

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

The first sentence gives a specific verb and resource ("List the custom fields defined in the archive") that is immediately distinguishable from siblings like list_tags and list_correspondents by the resource name alone. It doesn't explicitly name an alternative list tool, so it stops short of a 5, but the scope is unambiguous.

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

Usage Guidelines5/5

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

It explicitly routes the agent: use get_document to read a document's field values by field ID, and use search_documents with a concrete query example ("custom_fields.value:overdue") to find documents by field value. These are concrete when-to-use-this-vs-siblings signals with a worked example.

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