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tobee89

mcp-paperless-ngx

Search documents

search_documents
Read-onlyIdempotent

Search Paperless-ngx documents by full-text query or metadata filters. Returns compact summaries (id, title, tags, dates) to locate documents without flooding context.

Instructions

Find documents by full-text search, metadata filters, or both. This is the main entry point for every 'which documents ...' question. Returns a compact summary per document (id, title, IDs of correspondent/type/tags, dates) — NOT the OCR text, which would flood the context. Use get_document_content for the text of a specific document.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
queryNoFull-text search across document content and metadata. Supports the Paperless query syntax, e.g. 'invoice AND 2024', 'correspondent:telekom', 'created:[2024-01-01 TO 2024-12-31]'. Prefer this for 'find documents about X' questions.
orderingNoSort field, '-' prefixed for descending. Common: -created, -added, title, archive_serial_number.-created
is_taggedNofalse returns documents with no tags at all — the untriaged pile.
owner__idNoOnly documents owned by this user ID.
page_sizeNoDefault 25.
is_in_inboxNotrue returns documents still carrying an inbox tag. The usual starting point for triage.
more_like_idNoReturn documents similar to this document ID. Ignores the other filters.
tags__id__inNoOnly documents carrying AT LEAST ONE of these tag IDs.
extra_filtersNoAny additional Django-style filter the documents endpoint accepts, e.g. {'content__icontains': 'kündigung', 'created__year': 2024, 'mime_type': 'application/pdf'}. Use this for filters not listed above.
tags__id__allNoOnly documents carrying ALL of these tag IDs.
tags__id__noneNoExclude documents carrying any of these tag IDs.
content_previewNoInclude this many characters of OCR text per document. 0 disables it. Keep small.
added__date__gteNoAdded to Paperless on or after this date (YYYY-MM-DD).
added__date__lteNoAdded to Paperless on or before this date (YYYY-MM-DD).
storage_path__idNoExact storage path ID.
title__icontainsNoCase-insensitive substring match on the title only. Cheaper and stricter than query.
correspondent__idNoExact correspondent ID.
document_type__idNoExact document type ID.
created__date__gteNoCreated on or after this date (YYYY-MM-DD).
created__date__lteNoCreated on or before this date (YYYY-MM-DD).
custom_field_queryNoJSON-encoded custom field filter, e.g. '["due","range",["2024-08-01","2024-09-01"]]' or '["customer","icontains","acme"]'. See the Paperless API docs for the operator list.
archive_serial_numberNoExact archive serial number.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.1

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, and the description adds meaningful behavior beyond them: it returns a compact per-document summary and deliberately omits full OCR text to avoid flooding context. This is useful operational context for an agent deciding whether the result will fit the conversation.

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

Conciseness5/5

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

Three sentences with no filler. The core purpose, expected return shape, and the key alternative (get_document_content) are all present and front-loaded.

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?

For a 23-parameter tool with no output schema, the description covers the essential selection information: search modes, response summary structure, and the alternate tool for full text. Filtering and pagination details are carried by the schema, and the enumerated summary fields compensate for the missing output schema.

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 96%, so the schema already documents nearly every parameter; the baseline of 3 applies. The tool description adds a high-level statement about full-text and metadata filters but does not need to repeat individual 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?

States a specific action ('Find documents') plus the two search modes (full-text and metadata filters), so the resource and operation are unambiguous. It also distinguishes itself from get_document_content by noting it returns summaries, not OCR text. The 'main entry point for every "which documents..." question' framing makes the purpose immediately usable.

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?

The description clearly tells the agent this is the default for document-finding questions and explicitly points to get_document_content when OCR text is needed. It does not contrast with sibling tools like global_search or search_autocomplete, so some alternative routing remains implicit.

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

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