# Semantic Scholar

> Use this tool when you need to access academic literature and research findings to enhance AI assistant capabilities or support literature reviews and trend analysis. It provides a streamlined interface to query papers, authors, and citations through the Semantic Scholar database, offering efficient request handling and comprehensive academic data. Ideal for use cases requiring up-to-date research information and bibliometric data, such as building applications that necessitate scholarly information or powering AI-driven literature reviews.

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

## Description

This Semantic Scholar API MCP server, built with FastMCP, provides a streamlined interface for AI assistants to access academic literature through the Semantic Scholar database. Developed to bridge the gap between AI systems and scholarly research, it offers tools for querying papers, authors, and citations. The implementation stands out by leveraging FastMCP's efficient request handling and Semantic Scholar's comprehensive academic database. By exposing Semantic Scholar's capabilities through standardized MCP endpoints, it allows AI systems to easily incorporate up-to-date research findings and bibliometric data. This server is particularly useful for enhancing AI assistants with academic research capabilities, supporting literature reviews, trend analysis in scientific fields, or building applications that require access to scholarly information.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/benhaotang-semantic-scholar)
- **Repository:** <https://github.com/benhaotang/mcp-semantic-scholar-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": "benhaotang-semantic-scholar"
    }
  }
}
```

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