# Semantic Scholar

> Use this tool when you need to streamline academic research workflows and access comprehensive publication data. It solves problems related to paper discovery, author profiling, and citation analysis by providing filters, batch retrieval, and text snippet search capabilities. With support for authenticated and unauthenticated API access, it offers a robust interface for searching, retrieving, and analyzing academic papers, making it ideal for researchers, students, and academics.

Canonical page: https://skillsregistry.net/skills/fegizii-semantic-scholar  
JSON: https://api.skillsregistry.net/v1/skills/fegizii-semantic-scholar

## Description

Integrates with the Semantic Scholar Academic Graph API to enable comprehensive academic research workflows. Provides paper search with filters for publication type, year, venue, and citation count, batch paper retrieval, author search and detailed profiles, and citation analysis tools. Features text snippet search across papers and PDF download capabilities with smart filename generation and metadata embedding using PyPDF2. Supports both authenticated and unauthenticated API access with robust error handling and rate limiting guidance.

## Trust

- **Trust score (0–1):** 0.89
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/fegizii-semantic-scholar)
- **Repository:** <https://github.com/fegizii/semanticscholarmcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "fegizii-semantic-scholar"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/fegizii-semantic-scholar` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/fegizii-semantic-scholar/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt