[{"_1":2,"_352":-5,"_353":-5},"loaderData",{"_3":4,"_22":23,"_24":25,"_285":286},"root",{"_5":6,"_7":8},"toasts",[],"visitor",{"_9":10,"_11":12},"viewportWidth",1280,"visitorSession",{"_13":14,"_16":17,"_18":-5,"_19":20,"_21":-5},"attributes",[15],"BOT","id",8144035,"membership","referenceId","01977afc-0380-74ac-b6b6-379a0c651892","userAccount","routes/_public/_layout",{},"routes/_public/mcp/servers/~namespace/~slug/_pages/_layout",{"_26":27,"_81":-5,"_82":40,"_29":83,"_202":203,"_283":284},"availableLocales",[28,40,46,53,60,67,74],{"_29":30,"_33":37,"_38":39},"mcpServer",{"_31":32,"_33":34,"_35":36},"description","Ermöglicht Benutzern die Suche nach wissenschaftlichen Artikeln auf Plattformen wie arXiv mithilfe bestimmter Schlüsselwörter. Für die Zukunft ist die Integration weiterer wissenschaftlicher Datenbanken geplant.","name","MCP Scholarly Server","readme","[![MseeP.ai-Sicherheitsbewertungsabzeichen](https://mseep.net/pr/adityak74-mcp-scholarly-badge.png)](https://mseep.ai/app/adityak74-mcp-scholarly)\n\n# mcp-wissenschaftlicher MCP-Server\n\n[![Schmiedeabzeichen](https://smithery.ai/badge/mcp-scholarly)](https://smithery.ai/server/mcp-scholarly)\n\nEin MCP-Server zur Suche nach wissenschaftlichen Artikeln. Weitere wissenschaftliche Anbieter werden in Kürze hinzugefügt.\n\n![demo1.jpeg](examples/demo1.png)\n\n![Bild](https://github.com/user-attachments/assets/13202184-bc12-4530-b7c1-2ee698f3e1cc)\n\n![Sterngeschichte-202551](https://github.com/user-attachments/assets/f22d5796-017c-4c53-b230-101a09a28118)\n\n## Komponenten\n\n### Werkzeuge\n\nDer Server implementiert ein Tool:\n\n* search-arxiv: Durchsucht Arxiv nach Artikeln, die mit dem angegebenen Schlüsselwort in Zusammenhang stehen.\n * Nimmt \"Schlüsselwort\" als erforderliche String-Argumente\n\n## Schnellstart\n\n### Installieren\n\n#### Claude Desktop\n\nUnter MacOS: `~/Library/Application\\ Support/Claude/claude_desktop_config.json` Unter Windows: `%APPDATA%/Claude/claude_desktop_config.json`\n\noder wenn Sie Docker verwenden\n\n### Installation über Smithery\n\nSo installieren Sie mcp-scholarly für Claude Desktop automatisch über [Smithery](https://smithery.ai/server/mcp-scholarly) :\n\n```bash\nnpx -y @smithery/cli install mcp-scholarly --client claude\n```\n\n## Entwicklung\n\n### Erstellen und Veröffentlichen\n\nSo bereiten Sie das Paket für die Verteilung vor:\n\n1. Abhängigkeiten synchronisieren und Sperrdatei aktualisieren:\n\n```bash\nuv sync\n```\n\n2. Erstellen Sie Paketverteilungen:\n\n```bash\nuv build\n```\n\nDadurch werden Quell- und Wheel-Distributionen im Verzeichnis `dist/` erstellt.\n\n3. Auf PyPI veröffentlichen:\n\n```bash\nuv publish\n```\n\nHinweis: Sie müssen PyPI-Anmeldeinformationen über Umgebungsvariablen oder Befehlsflags festlegen:\n\n* Token: `--token` oder `UV_PUBLISH_TOKEN`\n* Oder Benutzername/Passwort: `--username` / `UV_PUBLISH_USERNAME` und `--password` / `UV_PUBLISH_PASSWORD`\n\n### Debuggen\n\nDa MCP-Server über stdio laufen, kann das Debuggen eine Herausforderung darstellen. Für ein optimales Debugging empfehlen wir dringend die Verwendung des [MCP Inspector](https://github.com/modelcontextprotocol/inspector) .\n\nSie können den MCP Inspector über [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) mit diesem Befehl starten:\n\n```bash\nnpx @modelcontextprotocol/inspector uv --directory /Users/adityakarnam/PycharmProjects/mcp-scholarly/mcp-scholarly run mcp-scholarly\n```\n\nBeim Start zeigt der Inspector eine URL an, auf die Sie in Ihrem Browser zugreifen können, um mit dem Debuggen zu beginnen.","German","tag","de-DE",{"_29":41,"_33":44,"_38":45},{"_31":42,"_33":34,"_35":43},"Enables users to search for academic articles on platforms like arXiv using specific keywords, with plans to integrate more scholarly databases in the future.","[![MseeP.ai Security Assessment Badge](https://mseep.net/pr/adityak74-mcp-scholarly-badge.png)](https://mseep.ai/app/adityak74-mcp-scholarly)\n\n# mcp-scholarly MCP server\n[![smithery badge](https://smithery.ai/badge/mcp-scholarly)](https://smithery.ai/server/mcp-scholarly)\n\nA MCP server to search for accurate academic articles. More scholarly vendors will be added soon.\n\n![demo1.jpeg](examples/demo1.png)\n\n![image](https://github.com/user-attachments/assets/13202184-bc12-4530-b7c1-2ee698f3e1cc)\n\n $\"Scholarly$ \n\n![star-history-202551](https://github.com/user-attachments/assets/f22d5796-017c-4c53-b230-101a09a28118)\n\n\n## Components\n\n### Tools\n\nThe server implements one tool:\n- search-arxiv: Search arxiv for articles related to the given keyword.\n - Takes \"keyword\" as required string arguments\n\n## Quickstart\n\n### Install\n\n#### Claude Desktop\n\nOn MacOS: `~/Library/Application\\ Support/Claude/claude_desktop_config.json`\nOn Windows: `%APPDATA%/Claude/claude_desktop_config.json`\n\n

Development/Unpublished Servers Configuration

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

\n\n

Published Servers Configuration

\n ```\n \"mcpServers\": {\n \"mcp-scholarly\": {\n \"command\": \"uvx\",\n \"args\": [\n \"mcp-scholarly\"\n ]\n }\n }\n ```\n

\n\nor if you are using Docker\n\n

Published Docker Servers Configuration

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

\n\n### Installing via Smithery\n\nTo install mcp-scholarly for Claude Desktop automatically via [Smithery](https://smithery.ai/server/mcp-scholarly):\n\n```bash\nnpx -y @smithery/cli install mcp-scholarly --client claude\n```\n\n## Development\n\n### Building and Publishing\n\nTo prepare the package for distribution:\n\n1. Sync dependencies and update lockfile:\n```bash\nuv sync\n```\n\n2. Build package distributions:\n```bash\nuv build\n```\n\nThis will create source and wheel distributions in the `dist/` directory.\n\n3. Publish to PyPI:\n```bash\nuv publish\n```\n\nNote: You'll need to set PyPI credentials via environment variables or command flags:\n- Token: `--token` or `UV_PUBLISH_TOKEN`\n- Or username/password: `--username`/`UV_PUBLISH_USERNAME` and `--password`/`UV_PUBLISH_PASSWORD`\n\n### Debugging\n\nSince MCP servers run over stdio, debugging can be challenging. For the best debugging\nexperience, we strongly recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector).\n\n\nYou can launch the MCP Inspector via [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) with this command:\n\n```bash\nnpx @modelcontextprotocol/inspector uv --directory /Users/adityakarnam/PycharmProjects/mcp-scholarly/mcp-scholarly run mcp-scholarly\n```\n\n\nUpon launching, the Inspector will display a URL that you can access in your browser to begin debugging.\n","English","en-US",{"_29":47,"_33":51,"_38":52},{"_31":48,"_33":49,"_35":50},"Permite a los usuarios buscar artículos académicos en plataformas como arXiv utilizando palabras clave específicas, con planes de integrar más bases de datos académicas en el futuro.","Servidor académico MCP","# Servidor MCP mcp-scholarly\n\n[![insignia de herrería](https://smithery.ai/badge/mcp-scholarly)](https://smithery.ai/server/mcp-scholarly)\n\nUn servidor MCP para buscar artículos académicos precisos. Próximamente se añadirán más proveedores académicos.\n\n![demo1.jpeg](examples/demo1.png)\n\n![imagen](https://github.com/user-attachments/assets/13202184-bc12-4530-b7c1-2ee698f3e1cc)\n\n![historia de las estrellas-202551](https://github.com/user-attachments/assets/f22d5796-017c-4c53-b230-101a09a28118)\n\n## Componentes\n\n### Herramientas\n\nEl servidor implementa una herramienta:\n\n* search-arxiv: busca en arxiv artículos relacionados con la palabra clave dada.\n * Toma \"palabra clave\" como argumento de cadena obligatorio\n\n## Inicio rápido\n\n### Instalar\n\n#### Escritorio de Claude\n\nEn MacOS: `~/Library/Application\\ Support/Claude/claude_desktop_config.json` En Windows: `%APPDATA%/Claude/claude_desktop_config.json`\n\no si estás usando Docker\n\n### Instalación mediante herrería\n\nPara instalar mcp-scholarly para Claude Desktop automáticamente a través de [Smithery](https://smithery.ai/server/mcp-scholarly) :\n\n```bash\nnpx -y @smithery/cli install mcp-scholarly --client claude\n```\n\n## Desarrollo\n\n### Construcción y publicación\n\nPara preparar el paquete para su distribución:\n\n1. Sincronizar dependencias y actualizar el archivo de bloqueo:\n\n```bash\nuv sync\n```\n\n2. Distribuciones de paquetes de compilación:\n\n```bash\nuv build\n```\n\nEsto creará distribuciones de origen y de rueda en el directorio `dist/` .\n\n3. Publicar en PyPI:\n\n```bash\nuv publish\n```\n\nNota: Deberás configurar las credenciales de PyPI a través de variables de entorno o indicadores de comando:\n\n* Token: `--token` o `UV_PUBLISH_TOKEN`\n* O nombre de usuario/contraseña: `--username` / `UV_PUBLISH_USERNAME` y `--password` / `UV_PUBLISH_PASSWORD`\n\n### Depuración\n\nDado que los servidores MCP se ejecutan en stdio, la depuración puede ser complicada. Para una experiencia óptima, recomendamos usar el [Inspector MCP](https://github.com/modelcontextprotocol/inspector) .\n\nPuede iniciar el Inspector MCP a través de [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) con este comando:\n\n```bash\nnpx @modelcontextprotocol/inspector uv --directory /Users/adityakarnam/PycharmProjects/mcp-scholarly/mcp-scholarly run mcp-scholarly\n```\n\nAl iniciarse, el Inspector mostrará una URL a la que podrá acceder en su navegador para comenzar a depurar.","Spanish","es-ES",{"_29":54,"_33":58,"_38":59},{"_31":55,"_33":56,"_35":57},"ユーザーは特定のキーワードを使用して arXiv などのプラットフォーム上の学術記事を検索できるようになります。将来的にはさらに多くの学術データベースを統合する予定です。","MCP 学術サーバー","# mcp-scholarly MCP サーバー\n\n[![鍛冶屋のバッジ](https://smithery.ai/badge/mcp-scholarly)](https://smithery.ai/server/mcp-scholarly)\n\n正確な学術論文を検索するためのMCPサーバー。近日中にさらに多くの学術ベンダーが追加される予定です。\n\n![デモ1.jpeg](examples/demo1.png)\n\n![画像](https://github.com/user-attachments/assets/13202184-bc12-4530-b7c1-2ee698f3e1cc)\n\n![星の歴史-202551](https://github.com/user-attachments/assets/f22d5796-017c-4c53-b230-101a09a28118)\n\n## コンポーネント\n\n### ツール\n\nサーバーは 1 つのツールを実装します。\n\n* search-arxiv: 指定したキーワードに関連する記事を arxiv で検索します。\n * 必須の文字列引数として「キーワード」を受け取ります\n\n## クイックスタート\n\n### インストール\n\n#### クロードデスクトップ\n\nMacOS の場合: `~/Library/Application\\ Support/Claude/claude_desktop_config.json` Windows の場合: `%APPDATA%/Claude/claude_desktop_config.json`\n\nまたはDockerを使用している場合\n\n### Smithery経由でインストール\n\n[Smithery](https://smithery.ai/server/mcp-scholarly)経由で Claude Desktop 用の mcp-scholarly を自動的にインストールするには:\n\n```bash\nnpx -y @smithery/cli install mcp-scholarly --client claude\n```\n\n## 発達\n\n### 建築と出版\n\n配布用のパッケージを準備するには:\n\n1. 依存関係を同期し、ロックファイルを更新します。\n\n```bash\nuv sync\n```\n\n2. パッケージディストリビューションをビルドします。\n\n```bash\nuv build\n```\n\nこれにより、 `dist/`ディレクトリにソースとホイールのディストリビューションが作成されます。\n\n3. PyPI に公開:\n\n```bash\nuv publish\n```\n\n注: 環境変数またはコマンドフラグを使用して PyPI 資格情報を設定する必要があります。\n\n* トークン: `--token`または`UV_PUBLISH_TOKEN`\n* またはユーザー名/パスワード: `--username` / `UV_PUBLISH_USERNAME`および`--password` / `UV_PUBLISH_PASSWORD`\n\n### デバッグ\n\nMCPサーバーはstdio経由で実行されるため、デバッグが困難になる場合があります。最適なデバッグ環境を実現するには、 [MCP Inspectorの](https://github.com/modelcontextprotocol/inspector)使用を強くお勧めします。\n\n次のコマンドを使用して、 [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm)経由で MCP Inspector を起動できます。\n\n```bash\nnpx @modelcontextprotocol/inspector uv --directory /Users/adityakarnam/PycharmProjects/mcp-scholarly/mcp-scholarly run mcp-scholarly\n```\n\n起動すると、ブラウザでアクセスしてデバッグを開始できる URL がインスペクタに表示されます。","Japanese","ja-JP",{"_29":61,"_33":65,"_38":66},{"_31":62,"_33":63,"_35":64},"사용자가 arXiv와 같은 플랫폼에서 특정 키워드를 사용하여 학술 논문을 검색할 수 있도록 하며, 향후에는 더 많은 학술 데이터베이스와 통합할 계획입니다.","MCP 학술 서버","# mcp-scholary MCP 서버\n\n[![대장간 배지](https://smithery.ai/badge/mcp-scholarly)](https://smithery.ai/server/mcp-scholarly)\n\n정확한 학술 논문을 검색하는 MCP 서버입니다. 더 많은 학술 검색 엔진이 곧 추가될 예정입니다.\n\n![데모1.jpeg](examples/demo1.png)\n\n![영상](https://github.com/user-attachments/assets/13202184-bc12-4530-b7c1-2ee698f3e1cc)\n\n![별-역사-202551](https://github.com/user-attachments/assets/f22d5796-017c-4c53-b230-101a09a28118)\n\n## 구성 요소\n\n### 도구\n\n서버는 하나의 도구를 구현합니다.\n\n* search-arxiv: 주어진 키워드와 관련된 기사를 arxiv에서 검색합니다.\n * 필수 문자열 인수로 \"키워드\"를 사용합니다.\n\n## 빠른 시작\n\n### 설치하다\n\n#### 클로드 데스크탑\n\nMacOS의 경우: `~/Library/Application\\ Support/Claude/claude_desktop_config.json` Windows의 경우: `%APPDATA%/Claude/claude_desktop_config.json`\n\n또는 Docker를 사용하는 경우\n\n### Smithery를 통해 설치\n\n[Smithery를](https://smithery.ai/server/mcp-scholarly) 통해 Claude Desktop에 mcp-scholarly를 자동으로 설치하려면:\n\n지엑스피1\n\n## 개발\n\n### 건축 및 출판\n\n배포를 위해 패키지를 준비하려면:\n\n1. 종속성 동기화 및 잠금 파일 업데이트:\n\n```bash\nuv sync\n```\n\n2. 패키지 배포 빌드:\n\n```bash\nuv build\n```\n\n이렇게 하면 `dist/` 디렉토리에 소스와 휠 배포판이 생성됩니다.\n\n3. PyPI에 게시:\n\n```bash\nuv publish\n```\n\n참고: 환경 변수나 명령 플래그를 통해 PyPI 자격 증명을 설정해야 합니다.\n\n* 토큰: `--token` 또는 `UV_PUBLISH_TOKEN`\n* 또는 사용자 이름/비밀번호: `--username` / `UV_PUBLISH_USERNAME` 및 `--password` / `UV_PUBLISH_PASSWORD`\n\n### 디버깅\n\nMCP 서버는 stdio를 통해 실행되므로 디버깅이 어려울 수 있습니다. 최상의 디버깅 환경을 위해서는 [MCP Inspector](https://github.com/modelcontextprotocol/inspector) 사용을 강력히 권장합니다.\n\n다음 명령을 사용하여 [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) 통해 MCP Inspector를 시작할 수 있습니다.\n\n```bash\nnpx @modelcontextprotocol/inspector uv --directory /Users/adityakarnam/PycharmProjects/mcp-scholarly/mcp-scholarly run mcp-scholarly\n```\n\nInspector를 실행하면 브라우저에서 접근하여 디버깅을 시작할 수 있는 URL이 표시됩니다.","Korean","ko-KR",{"_29":68,"_33":72,"_38":73},{"_31":69,"_33":70,"_35":71},"Позволяет пользователям искать научные статьи на таких платформах, как arXiv, по определенным ключевым словам, а в будущем планируется интегрировать больше научных баз данных.","MCP Научный сервер","[![Значок оценки безопасности MseeP.ai](https://mseep.net/pr/adityak74-mcp-scholarly-badge.png)](https://mseep.ai/app/adityak74-mcp-scholarly)\n\n# mcp-scholarly сервер MCP\n\n[![значок кузнеца](https://smithery.ai/badge/mcp-scholarly)](https://smithery.ai/server/mcp-scholarly)\n\nСервер MCP для поиска точных академических статей. Скоро будут добавлены другие поставщики научных статей.\n\n![demo1.jpeg](examples/demo1.png)\n\n![изображение](https://github.com/user-attachments/assets/13202184-bc12-4530-b7c1-2ee698f3e1cc)\n\n![star-history-202551](https://github.com/user-attachments/assets/f22d5796-017c-4c53-b230-101a09a28118)\n\n## Компоненты\n\n### Инструменты\n\nНа сервере реализован один инструмент:\n\n* search-arxiv: Поиск в arxiv статей, связанных с указанным ключевым словом.\n * Принимает «ключевое слово» в качестве обязательных строковых аргументов\n\n## Быстрый старт\n\n### Установить\n\n#### Клод Десктоп\n\nВ MacOS: `~/Library/Application\\ Support/Claude/claude_desktop_config.json` В Windows: `%APPDATA%/Claude/claude_desktop_config.json`\n\nили если вы используете Docker\n\n### Установка через Smithery\n\nЧтобы автоматически установить mcp-scholarly для Claude Desktop через [Smithery](https://smithery.ai/server/mcp-scholarly) :\n\n```bash\nnpx -y @smithery/cli install mcp-scholarly --client claude\n```\n\n## Разработка\n\n### Строительство и издательское дело\n\nЧтобы подготовить пакет к распространению:\n\n1. Синхронизируем зависимости и обновляем файл блокировки:\n\n```bash\nuv sync\n```\n\n2. Сборка дистрибутивов пакетов:\n\n```bash\nuv build\n```\n\nЭто создаст исходный код и дистрибутивы wheel в каталоге `dist/` .\n\n3. Опубликовать в PyPI:\n\n```bash\nuv publish\n```\n\nПримечание: вам необходимо задать учетные данные PyPI с помощью переменных среды или флагов команд:\n\n* Токен: `--token` или `UV_PUBLISH_TOKEN`\n* Или имя пользователя/пароль: `--username` / `UV_PUBLISH_USERNAME` и `--password` / `UV_PUBLISH_PASSWORD`\n\n### Отладка\n\nПоскольку серверы MCP работают через stdio, отладка может быть сложной. Для лучшего опыта отладки мы настоятельно рекомендуем использовать [MCP Inspector](https://github.com/modelcontextprotocol/inspector) .\n\nВы можете запустить MCP Inspector через [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) с помощью этой команды:\n\n```bash\nnpx @modelcontextprotocol/inspector uv --directory /Users/adityakarnam/PycharmProjects/mcp-scholarly/mcp-scholarly run mcp-scholarly\n```\n\nПосле запуска Инспектор отобразит URL-адрес, к которому вы можете перейти в своем браузере, чтобы начать отладку.","Russian","ru-RU",{"_29":75,"_33":79,"_38":80},{"_31":76,"_33":77,"_35":78},"使用户能够使用特定关键词在 arXiv 等平台上搜索学术文章，并计划在未来整合更多学术数据库。","MCP学术服务器","# mcp-scholarly MCP 服务器\n\n[![铁匠徽章](https://smithery.ai/badge/mcp-scholarly)](https://smithery.ai/server/mcp-scholarly)\n\n一个 MCP 服务器，用于搜索精准的学术文章。更多学术供应商即将添加。\n\n![演示1.jpeg](examples/demo1.png)\n\n![图像](https://github.com/user-attachments/assets/13202184-bc12-4530-b7c1-2ee698f3e1cc)\n\n![明星历史-202551](https://github.com/user-attachments/assets/f22d5796-017c-4c53-b230-101a09a28118)\n\n## 成分\n\n### 工具\n\n服务器实现了一个工具：\n\n* search-arxiv：在 arxiv 中搜索与给定关键字相关的文章。\n * 将“关键字”作为必需的字符串参数\n\n## 快速入门\n\n### 安装\n\n#### 克劳德桌面\n\n在 MacOS 上： `~/Library/Application\\ Support/Claude/claude_desktop_config.json`在 Windows 上： `%APPDATA%/Claude/claude_desktop_config.json`\n\n或者如果你正在使用 Docker\n\n### 通过 Smithery 安装\n\n要通过[Smithery](https://smithery.ai/server/mcp-scholarly)自动为 Claude Desktop 安装 mcp-scholarly：\n\n```bash\nnpx -y @smithery/cli install mcp-scholarly --client claude\n```\n\n## 发展\n\n### 构建和发布\n\n准备分发包：\n\n1. 同步依赖项并更新锁文件：\n\n```bash\nuv sync\n```\n\n2. 构建软件包分发版：\n\n```bash\nuv build\n```\n\n这将在`dist/`目录中创建源和轮子分布。\n\n3. 发布到 PyPI：\n\n```bash\nuv publish\n```\n\n注意：您需要通过环境变量或命令标志设置 PyPI 凭据：\n\n* 令牌： `--token`或`UV_PUBLISH_TOKEN`\n* 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MCP directory API