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    Mcp Scholarly

    A MCP server to search for accurate academic articles. Python-based implementation.

    160 stars
    Python
    Updated Nov 3, 2025

    Documentation

    MseeP.ai Security Assessment Badge

    mcp-scholarly MCP server

    smithery badge

    A MCP server to search for accurate academic articles. More scholarly vendors will be added soon.

    demo1.jpeg

    image

    star-history-202551

    Components

    Tools

    The server implements one tool:

    • search-arxiv: Search arxiv for articles related to the given keyword.
    • Takes "keyword" as required string arguments

    Quickstart

    Install

    Claude Desktop

    On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json

    On Windows: %APPDATA%/Claude/claude_desktop_config.json

    Development/Unpublished Servers Configuration

    code
    "mcpServers": {
        "mcp-scholarly": {
          "command": "uv",
          "args": [
            "--directory",
            "/Users/adityakarnam/PycharmProjects/mcp-scholarly/mcp-scholarly",
            "run",
            "mcp-scholarly"
          ]
        }
      }

    Published Servers Configuration

    code
    "mcpServers": {
        "mcp-scholarly": {
          "command": "uvx",
          "args": [
            "mcp-scholarly"
          ]
        }
      }

    or if you are using Docker

    Published Docker Servers Configuration

    code
    "mcpServers": {
        "mcp-scholarly": {
          "command": "docker",
          "args": [
            "run", "--rm", "-i",
            "mcp/scholarly"
          ]
        }
      }

    Installing via Smithery

    To install mcp-scholarly for Claude Desktop automatically via Smithery:

    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.

    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.

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