# Academic MCP Server

> Use this tool when you need to efficiently search and retrieve academic research across multiple databases, or when faced with complex research workflows that require advanced filtering and citation analysis. It provides a unified interface to access PubMed, arXiv, bioRxiv, medRxiv, and Semantic Scholar, allowing for streamlined metadata retrieval and PDF downloads. Ideal for AI assistants tasked with comprehensive research tasks, this tool simplifies the process of finding and analyzing relevant academic literature.

Canonical page: https://skillsregistry.net/skills/nanyang12138-academic-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/nanyang12138-academic-mcp-server

## Description

Enables AI assistants to search across multiple academic databases (PubMed, arXiv, bioRxiv, medRxiv, Semantic Scholar) through a unified interface. Supports advanced filtering, metadata retrieval, PDF downloads, and comprehensive research workflows with citation analysis.

## Trust

- **Trust score (0–1):** 0.41
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/c86qykspvr)
- **Repository:** <https://github.com/nanyang12138/Academic-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": "nanyang12138-academic-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/nanyang12138-academic-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/nanyang12138-academic-mcp-server/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