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Academic Literature MCP (Multi-site)

Academic Literature MCP (Multi-site)

by wkkdmx

structured_search

Search scholarly records across multiple academic databases using precise Boolean field queries on title, author, DOI, year, and more to filter results by exact criteria.

Instructions

布尔表达式精确检索:叶子 {field,value,match},组合 {op:and|or|not,items}。

字段:title、topic、abstract、author(s)、source、doi、document_type、 issn、accession、organization、pmid、year。match 为 phrase(默认)或 exact。

Input Schema

NameRequiredDescriptionDefault
siteNo
sortNorelevance
limitNo
optionsNo
year_toNo
year_fromNo
expressionYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose meaningful behavior for the expression itself: allowed operators, the default of `match: phrase` versus `exact`, and the exact field vocabulary. It says nothing about what happens on malformed expressions, how `site` scopes results, auth/rate limits, or pagination behavior, which leaves substantial behavioral ground uncovered.

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?

Two compact sentences with the grammar front-loaded and the valid field list following it; every element is load-bearing. The structure is terse but readable, with no filler.

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 a nested, free-form object as the required argument, the description gives the minimum an agent needs to build a valid expression. It stops short of covering the six sibling parameters and the year_from/year_to versus `year` overlap, which is a real ambiguity for a 7-parameter tool, though the existing output schema reduces the need to describe results.

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% across 7 parameters, so six of them (site, sort, limit, options, year_from, year_to) are documented nowhere. The description compensates strongly for the required `expression` parameter by spelling out its nested shape and field names, but it never clarifies how year_from/year_to relate to the `year` field inside the expression or what `options` accepts, so the gap is only partly filled.

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 names a specific mechanism: boolean-expression retrieval where a leaf is {field,value,match} and a node is {op:and|or|not,items}, and it enumerates the queryable fields. An agent can tell this is the precise/structured query tool, but nothing in the text distinguishes it from the sibling `search` tool, so it falls short of a 5.

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

Usage Guidelines2/5

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

There is no explicit statement about when to use this tool instead of `search` or `search_results`, and no exclusions or preconditions. Precise boolean semantics are implied by the grammar, but the choice between this and a plain keyword search is left entirely to inference.

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