# scholar-search-mcp

> scholar-search-mcp — silung-scholar-search-mcp. Use this tool when you need to integrate AI assistants with academic paper search functionality, enabling them to retrieve relevant paper metadata. It solves the problem of efficient academic paper discovery and retrieval, providing inputs such as search queries and outputs like relevant paper metadata. Ideal for use cases where AI agents require access to academic research, such as research assistance or literature review tasks.

Canonical page: https://skillsregistry.net/skills/silung-scholar-search-mcp  
JSON: https://api.skillsregistry.net/v1/skills/silung-scholar-search-mcp

## Description

An MCP server for academic paper search that integrates with AI assistants (e.g., Claude Code, Cursor), enabling them to search and retrieve academic paper metadata.

## Trust

- **Trust score (0–1):** 0.85
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** search
- **Updated:** 2026-09-24

## Source

- **Source listing:** [GitHub](https://github.com/Silung/scholar-search-mcp)

## 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": "silung-scholar-search-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/silung-scholar-search-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/silung-scholar-search-mcp/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