# Academic Paper Search

> Use this tool when you need to efficiently search and retrieve academic papers from multiple sources, solving problems such as literature reviews and research trend analysis. It takes in search queries, topics, and date ranges as inputs and outputs structured metadata, providing a standardized interface for AI assistants and applications. This tool is ideal for use cases that require access to scientific literature, enhancing the capabilities of AI models in academic and research contexts.

Canonical page: https://skillsregistry.net/skills/afrise-academic-search  
JSON: https://api.skillsregistry.net/v1/skills/afrise-academic-search

## Description

This MCP server provides academic paper search and retrieval functionality across multiple sources like Semantic Scholar and Crossref. Built with Python using the FastMCP framework, it offers tools for searching papers, fetching detailed metadata, and filtering by topic and date range. The implementation focuses on delivering structured academic information through a standardized interface, making it particularly useful for AI assistants and applications that require access to scientific literature. By connecting to established academic APIs, this server enables use cases such as literature reviews, research trend analysis, and citation management, enhancing the capabilities of AI models in academic and research contexts.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

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

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/afrise-academic-search)
- **Repository:** <https://github.com/afrise/academic-search-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": "afrise-academic-search"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/afrise-academic-search` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/afrise-academic-search/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