# mcp-scholarly

> MCP Server

This repository hosts mcp-scholarly, an MCP server designed to search for accurate academic articles, initially focusing on arXiv and planning to incorporate more scholarly vendors in the future.

## Overview

- **Category:** Search & Knowledge
- **Language:** Python
- **Stars:** 185
- **Forks:** 6
- **Owner:** adityak74
- **GitHub:** https://github.com/adityak74/mcp-scholarly
- **Created:** 2025-01-01T05:34:06+00:00
- **Updated:** 2025-03-28T07:50:05+00:00
- **Source:** https://model-context-protocol.com/servers/mcp-server-search-accurate-academic-articles

## Setup

## Setup

#### Claude Desktop

On MacOS: `~/Library/Application\ Support/Claude/claude_desktop_config.json`
On Windows: `%APPDATA%/Claude/claude_desktop_config.json`

<details>
  <summary>Development/Unpublished Servers Configuration</summary>
  ```
  "mcpServers": {
    "mcp-scholarly": {
      "command": "uv",
      "args": [
        "--directory",
        "/Users/adityakarnam/PycharmProjects/mcp-scholarly/mcp-scholarly",
        "run",
        "mcp-scholarly"
      ]
    }
  }
  ```
</details>

<details>
  <summary>Published Servers Configuration</summary>
  ```
  "mcpServers": {
    "mcp-scholarly": {
      "command": "uvx",
      "args": [
        "mcp-scholarly"
      ]
    }
  }
  ```
</details>

or if you are using Docker

<details>
  <summary>Published Docker Servers Configuration</summary>
  ```
  "mcpServers": {
    "mcp-scholarly": {
      "command": "docker",
      "args": [
        "run", "--rm", "-i",
        "mcp/scholarly"
      ]
    }
  }
  ```
</details>

### Installing via Smithery

To install mcp-scholarly for Claude Desktop automatically via [Smithery](https://smithery.ai/server/mcp-scholarly):

```bash
npx -y @smithery/cli install mcp-scholarly --client claude
```

## Development

### Building and Publishing

To prepare the package for distribution:

1. Sync dependencies and update lockfile:
```bash
uv sync
```

2. Build package distributions:
```bash
uv build
```

This will create source and wheel distributions in the `dist/` directory.

3. Publish to PyPI:
```bash
uv publish
```

Note: You'll need to set PyPI credentials via environment variables or command flags:
- Token: `--token` or `UV_PUBLISH_TOKEN`
- Or username/password: `--username`/`UV_PUBLISH_USERNAME` and `--password`/`UV_PUBLISH_PASSWORD`

### Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging
experience, we strongly recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector).

You can launch the MCP Inspector via [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) with this command:

```bash
npx @modelcontextprotocol/inspector uv --directory /Users/adityakarnam/PycharmProjects/mcp-scholarly/mcp-scholarly run mcp-scholarly
```

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.

## Tools

## Available Tools

		1. search-arxiv: Search arxiv for articles related to the given keyword.