# Semantic Scholar

> Use this tool when you need to access and analyze academic literature at scale, providing features like paper search, citation analysis, and author information retrieval through a standardized interface. It solves problems such as literature reviews, trend analysis, and citation network exploration, and is particularly valuable for research and academic applications. The tool accepts queries and filters as inputs and returns relevant academic papers, authors, and citations as outputs.

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

## Description

This Semantic Scholar MCP server, developed by an unnamed creator, provides a robust interface to the Semantic Scholar Academic Graph API. Built with Python using FastMCP and httpx, it offers tools for paper search, citation analysis, author information retrieval, and paper recommendations. The server implements advanced features like complex filtering, customizable ranking strategies, and efficient batch operations. By abstracting Semantic Scholar API operations into a standardized MCP format, it enables AI systems to easily access and analyze academic literature at scale. This implementation is particularly valuable for research and academic applications, facilitating use cases such as literature reviews, trend analysis, citation network exploration, and personalized paper recommendations.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-09-01

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/yuzongmin-semantic-scholar)
- **Repository:** <https://github.com/zongmin-yu/semantic-scholar-fastmcp-mcp-server>

## 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": "yuzongmin-semantic-scholar"
    }
  }
}
```

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

---
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