Paper Search MCP

search_semantic_scholar

Search academic papers by query, filter by year or field of study, and get citation data from Semantic Scholar.

Instructions

Search Semantic Scholar for academic papers with citation data

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_semantic_scholar"
  }
}

Input Schema

Name	Required	Description
`year`	No	Year filter (e.g., "2023", "2020-2023")
`query`	Yes	Search query string
`maxResults`	No	Maximum number of results to return
`fieldsOfStudy`	No	Fields of study filter (e.g., ["Computer Science", "Biology"])

Schema Changelog

Changes observed during successful MCP inspections.

First observedDec 29, 2025

TDQS

C2.9/5.0

Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'Search' implies a read-only operation, the description doesn't mention important behavioral aspects like rate limits, authentication requirements, response format, pagination behavior, or error conditions. The mention of 'citation data' hints at what's returned but doesn't provide operational details.

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, efficient sentence that communicates the core functionality without unnecessary words. It's appropriately sized for a search tool and front-loads the essential information. Every word earns its place in this concise statement.

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

Completeness2/5

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

For a search tool with 4 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what kind of results to expect, how citation data is presented, or how this tool differs from the many other search tools available. The lack of behavioral context and usage guidance leaves significant gaps for an AI agent trying to use this tool effectively.

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 4 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema descriptions. It mentions 'citation data' which relates to output rather than input parameters. Baseline score of 3 is appropriate when schema does the heavy lifting.

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 clearly states the action ('Search') and resource ('Semantic Scholar for academic papers'), and specifies the type of data returned ('with citation data'). However, it doesn't explicitly differentiate this tool from its many sibling search tools (e.g., search_arxiv, search_pubmed) beyond mentioning Semantic Scholar specifically.

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?

The description provides no guidance on when to use this tool versus the many alternative search tools available on the server (search_arxiv, search_pubmed, search_google_scholar, etc.). There's no mention of Semantic Scholar's specific strengths, coverage, or when it might be preferred over other academic search tools.

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