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ScrapingDog-MCP

ScrapingDog-MCP

by alessandrobenigni
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

google_scholar_author_citation

Fetch citation metrics and individual article citation details for a Google Scholar author by providing the author ID and citation ID.

Instructions

Retrieves citation metrics (h-index, i10-index, yearly citation graph) and individual article citation detail for a Google Scholar author, using view_op=view_citation on the author endpoint. [Credits: Not explicitly stated on this documentation page.] Notes: SAME endpoint URL as google_scholar_author (https://api.scrapingdog.com/google_scholar/author) - see ambiguity note on that tool. citation_id format observed as '<author_id>:<opaque_token>' (e.g. LSsXyncAAAAJ:2osOgNQ5qMEC). Returns: { cited_by: { table: [ { citations: { all, since_2019 } }, { h_index: { all, since_2019 } }, { i10_index: { all, since_2019 } } ], graph: [ { year, citations } ] } }

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": {
      "author_id": "<author_id>",
      "view_op": "<view_op>",
      "citation_id": "<citation_id>"
    },
    "name": "google_scholar_author_citation"
  }
}

Input Schema

NameRequiredDescriptionDefault
view_opYesSection of the page to access: view_citation (display citation detail; requires citation_id) or list_colleagues (view all co-authors).
languageNoLanguage of the results, e.g. en, es, fr, de. See Google Language Page. (default: en)
author_idYesAuthor ID of the person to get data for.
citation_idYesID for fetching an individual article's citation detail. Mandatory when view_op=view_citation. Obtainable from google_scholar_author's articles[].citation_id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.4/5.0
Behavior4/5

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

No annotations exist, so the description must fully disclose behavior. It does so by describing the read-only retrieval operation, the return structure, and the required parameters. It could mention rate limits or authentication, but for a simple data retrieval tool, it's sufficiently transparent.

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?

The description is multi-sentence but each sentence adds necessary information: purpose, endpoint note, citation_id format, and output structure. It is front-loaded with the core action. Slightly verbose but not wasteful.

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 no output schema, the description provides a detailed breakdown of the return structure. It covers all required parameters and their interrelation. Missing error handling or edge cases, but sufficient for typical use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage with descriptions, but the description adds significant value by explaining the citation_id format (author_id:opaque_token) and its source (from google_scholar_author's articles). This extra context helps the agent use the parameters correctly.

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 tool retrieves citation metrics (h-index, i10-index, yearly graph) and article citation details, using view_op=view_citation on the author endpoint. This distinguishes it from siblings like google_scholar_author (profile retrieval) and google_scholar_cite (citation format).

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 explains that citation_id is required and obtainable from google_scholar_author, and points to an ambiguity note about the shared endpoint. While it doesn't explicitly list when not to use, it provides enough context to avoid confusion with similar tools.

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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