Paper Search MCP

get_citations

Retrieve citation data (citation count, references, venue) for a paper by DOI using Semantic Scholar.

Instructions

Retrieve citation data (citation count, references, venue) for a paper by DOI using Semantic Scholar

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": {
      "doi": "<doi>"
    },
    "name": "get_citations"
  }
}

Input Schema

Name	Required	Description	Default
`doi`	Yes	DOI (Digital Object Identifier)
`forceRefresh`	No	Bypass the cache and fetch fresh data (default: false)

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.2.7-patchAug 20, 2026

TDQS

A4/5.0

Behavior3/5

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

With no annotations provided, the description must carry the full burden. It confirms it is a read operation (no side effects), but it does not disclose caching behavior, rate limits, or error handling. The mention of Semantic Scholar implies an external dependency but no caveats. This is a modest gap given the simple nature of the tool.

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?

A single sentence that is front-loaded with the core action and output, followed by the input method and source. No wasted words, length is appropriate for the tool's simplicity.

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 tool with 2 parameters, no output schema, and no annotations, the description provides sufficient context: it specifies what data is returned and that input is a DOI. The forceRefresh parameter is explained in the schema, and the description implies a single-paper lookup. Missing details like potential errors or rate limits are minor for this scope, making the description complete enough.

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 both parameters (doi, forceRefresh) already documented in the schema. The description adds minimal extra meaning beyond confirming the DOI is for the paper and that data comes from Semantic Scholar. Since the schema fully covers parameters, the baseline of 3 is appropriate; the description does not enhance parameter understanding.

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 the action (retrieve citation data), the specific resource (a paper by DOI), and the data fields returned (citation count, references, venue). It also names the external service (Semantic Scholar), which distinguishes it from siblings like get_paper_by_doi that likely return different metadata.

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 implicitly conveys when to use it: when you have a DOI and need citation metrics. It does not explicitly mention when not to use it or alternatives, but the phrase 'citation data' differentiates it from general paper lookups. No exclusions are given, but the context is clear enough for an agent to choose it over search tools.

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