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openpapers-mcp

openpapers-mcp

by Scentless-trick128
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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search_papers

Search academic papers by relevance via OpenAlex, returning DOI, title, authors, year, citation count, and OA status. Filter by publication year range.

Instructions

Search academic papers by relevance via OpenAlex. Returns a compact list with DOI, title, authors, year, venue, citation count, OA status, and top concepts. Use year_from/year_to to constrain the publication year.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "search_papers"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesFree-text search query, e.g. 'transformer attention mechanism'.
year_toNoInclusive upper publication year bound.
year_fromNoInclusive lower publication year bound.
num_resultsNoMax number of results (1..50).

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations provided, the description takes on the burden of explaining behavior. It discloses that the tool 'Returns a compact list' with specific fields (DOI, title, authors, year, venue, citation count, OA status, top concepts), and mentions relevance-based search. This goes beyond a mere definition, though it omits details like rate limits or authentication requirements.

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 two sentences long, front-loaded with the main purpose, and contains no redundant or filler content. Every sentence provides distinct value: purpose, return contents, and a filtering hint.

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 the tool's moderate complexity (4 parameters) and the presence of an output schema, the description supplies key information about search behavior and return fields. It lacks explicit usage guidance for when to use this tool over siblings, but overall covers the essential context well.

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%, so the schema already documents all parameters. The description adds a minor clarification for year_from/year_to ('constrain the publication year'), but this does not significantly exceed the schema's existing descriptions. Baseline 3 is appropriate.

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 starts with 'Search academic papers by relevance via OpenAlex', which clearly identifies the verb (search), resource (academic papers), and scope (relevance, OpenAlex). This distinguishes it from sibling tools like get_paper (specific paper retrieval), find_oa_pdf, and download_pdf, which have different purposes.

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 usage for searching academic papers by relevance, and gives a parameter hint ('Use year_from/year_to to constrain the publication year'), but does not explicitly state when to choose this tool over siblings or provide exclusions. The guidance is implied rather than explicit.

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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