# paperSearch

> Use this tool when you need to efficiently search and analyze academic papers, resolve biomedical entities, and extract relationships from scholarly articles. It solves problems related to information retrieval, entity disambiguation, and knowledge graph construction in the biomedical domain. The tool takes search queries and paper IDs as input and outputs relevant papers, entities, and citation graphs, making it ideal for AI agents working on research-intensive tasks.

Canonical page: https://skillsregistry.net/skills/freddiewho-searchpaper  
JSON: https://api.skillsregistry.net/v1/skills/freddiewho-searchpaper

## Description

Enables AI coding agents to search academic papers, resolve biomedical entities, mine relations, and traverse citation graphs using Semantic Scholar and PubTator3, with local caching for reproducibility.

## Trust

- **Trust score (0–1):** 0.61
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/xn5p2vsopw)
- **Repository:** <https://github.com/FreddieWho/SearchPaper>

## 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": "freddiewho-searchpaper"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/freddiewho-searchpaper` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/freddiewho-searchpaper/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