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paperlib-mcp

paperlib-mcp

by polarizetech
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

library

Search your stored papers by title, author, or full text to locate relevant research already in your library.

Instructions

Search papers already held (titles and authors; optionally inside stored full text).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "library"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
queryNo
full_textNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It does disclose the optional full-text search behavior and the scope limitation to already-held papers, which is helpful. However, it doesn't mention default limit behavior, pagination, or what happens when query is empty.

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?

The description is a single, well-structured sentence that front-loads the core action and scope, then adds the optional full-text detail. Every word earns its place with no redundancy.

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

Completeness3/5

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

The tool has an output schema, so return values are covered elsewhere. The description covers the core search scope and the optional full-text mode, but with no annotations and no mention of default behavior or result ordering, an agent has only partial context for invoking it correctly.

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 0%, so the description must compensate. It explains the 'full_text' parameter's purpose (searching inside stored full text) and implies 'query' is the search term. However, it doesn't clarify the 'limit' parameter's behavior or the meaning of an empty query, leaving some semantics to inference.

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 description states a specific verb ('Search') and resource ('papers already held'), and clarifies the search scope (titles and authors, optionally full text). It is clear enough to distinguish from a general web search, though it doesn't explicitly name a sibling alternative.

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

Usage Guidelines3/5

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

The description implies this is for searching the user's existing library rather than external sources, which is useful context. However, it doesn't explicitly state when to use this tool versus the sibling 'search' tool, nor does it provide exclusions or alternative routing.

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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