[{"_1":2,"_569":-5,"_570":-5},"loaderData",{"_3":4,"_22":23,"_24":25,"_419":420},"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",6792357,"membership","referenceId","0196f466-800e-734e-ba2f-2b60637c4a9f","userAccount","routes/_public/_layout",{},"routes/_public/mcp/servers/~namespace/~slug/_pages/_layout",{"_26":27,"_77":-5,"_78":40,"_29":79,"_337":338,"_418":191},"availableLocales",[28,40,46,52,59,65,71],{"_29":30,"_33":37,"_38":39},"mcpServer",{"_31":32,"_33":34,"_35":36},"description","Der Phoenix MCP Server ist eine Implementierung des Model Context Protocol für die Arize Phoenix-Plattform. Er bietet eine einheitliche Schnittstelle zu den Funktionen von Phoenix.\n\nSie können Phoenix MCP Server für Folgendes verwenden:\n\nPrompts Management: Erstellen, Auflisten, Aktualisieren und Iterieren von Prompts Datasets: Erkunden Sie Datasets und synte","name","@arizeai/phoenix-mcp","readme","[![Lizenz](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://github.com/Arize-ai/phoenix/blob/main/js/packages/phoenix-mcp/LICENSE)\n\nDer Phoenix MCP Server ist eine Implementierung des Model Context Protocol für die Arize Phoenix-Plattform. Er bietet eine einheitliche Schnittstelle zu den Funktionen von Phoenix.\n\nSie können Phoenix MCP Server für Folgendes verwenden:\n\n* **Eingabeaufforderungsverwaltung** : Erstellen, Auflisten, Aktualisieren und Iterieren von Eingabeaufforderungen\n* **Datensätze** : Erkunden Sie Datensätze und synthetisieren Sie neue Beispiele\n* **Experimente** : Ziehen Sie Experimentergebnisse und visualisieren Sie diese mit Hilfe eines LLM\n\nSie finden keinen Anwendungsfall? `@arizeai/phoenix-mcp` ist [Open Source](https://github.com/Arize-ai/phoenix) ! Probleme und PRs sind willkommen.\n\n## Installation\n\nDieser MCP-Server kann mit `npx` verwendet und direkt in Clients wie Claude Desktop, Cursor und mehr integriert werden.\n\n```json\n{\n \"mcpServers\": {\n \"phoenix\": {\n \"command\": \"npx\",\n \"args\": [\n \"-y\",\n \"@arizeai/phoenix-mcp@latest\",\n \"--baseUrl\",\n \"https://my-phoenix.com\",\n \"--apiKey\",\n \"your-api-key\"\n ]\n }\n }\n```\n\n## Entwicklung\n\n## Installieren\n\nDieses Paket wird über einen pnpm-Arbeitsbereich verwaltet.\n\n```sh\n// From the /js/ directory\npnpm install\npnpm build\n```\n\nDies muss nur wiederholt werden, wenn sich Abhängigkeiten ändern oder eine Änderung am Phoenix-Client erfolgt.\n\n### Gebäude\n\nSo erstellen Sie das Projekt:\n\n```sh\npnpm build\n```\n\n### Entwicklungsmodus\n\nSo führen Sie die Ausführung im Entwicklungsmodus aus:\n\n```bash\npnpm dev\n```\n\n### Debuggen\n\nSie können den MCP-Inspektor wie folgt erstellen und ausführen:\n\n```bash\npnpm inspect\n```\n\n## Umgebungsvariablen\n\nBei der Entwicklung benötigt der Server folgende Umgebungsvariablen:\n\n* `PHOENIX_API_KEY` : Ihr Phoenix-API-Schlüssel\n* `PHOENIX_BASE_URL` : Die Basis-URL für Phoenix\n\nStellen Sie sicher, dass Sie diese in einer `.env` Datei festlegen. Siehe `.env.example` .\n\n# Lizenz\n\nApache 2.0","German","tag","de-DE",{"_29":41,"_33":44,"_38":45},{"_31":42,"_33":34,"_35":43},"Phoenix MCP Server is an implementation of the Model Context Protocol for the Arize Phoenix platform. It provides a unified interface to Phoenix's capabilites.\n\nYou can use Phoenix MCP Server for:\n\nPrompts Management: Create, list, update, and iterate on prompts\nDatasets: Explore datasets, and synte","

\n
\n \n \n \n \n $\"Arize$ \n \n \n
\n Arize Phoenix MCP Server\n
\n

\n\n[![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://github.com/Arize-ai/phoenix/blob/main/js/packages/phoenix-mcp/LICENSE)\n $\"MCP$ \n\nPhoenix MCP Server is an implementation of the Model Context Protocol for the Arize Phoenix platform. It provides a unified interface to Phoenix's capabilites.\n\nYou can use Phoenix MCP Server for:\n\n- **Prompts Management**: Create, list, update, and iterate on prompts\n- **Datasets**: Explore datasets, and syntesize new examples\n- **Experiments**: Pull experiment results and visualize them with the help of an LLM\n\nDon't see a use-case covered? `@arizeai/phoenix-mcp` is [open-source](https://github.com/Arize-ai/phoenix)! Issues and PRs welcome.\n\n## Installation\n\nThis MCP server can be used using `npx` and can be directly integrated with clients like Claude Desktop, Cursor, and more.\n\n```json\n{\n \"mcpServers\": {\n \"phoenix\": {\n \"command\": \"npx\",\n \"args\": [\n \"-y\",\n \"@arizeai/phoenix-mcp@latest\",\n \"--baseUrl\",\n \"https://my-phoenix.com\",\n \"--apiKey\",\n \"your-api-key\"\n ]\n }\n }\n```\n\n## Development\n\n## Install\n\nThis package is managed via a pnpm workspace.\n\n```sh\n// From the /js/ directory\npnpm install\npnpm build\n```\n\nThis only needs to be repeated if dependencies change or there is a change to the phoenix-client.\n\n### Building\n\nTo build the project:\n\n```sh\npnpm build\n```\n\n### Development Mode\n\nTo run in development mode:\n\n```bash\npnpm dev\n```\n\n### Debugging\n\nYou can build and run the MCP inspector using the following:\n\n```bash\npnpm inspect\n```\n\n## Environment Variables\n\nWhen developing, the server requires the following environment variables:\n\n- `PHOENIX_API_KEY`: Your Phoenix API key\n- `PHOENIX_BASE_URL`: The base URL for Phoenix\n\nMake sure to set these in a `.env` file. See `.env.example`.\n\n# License\n\nApache 2.0\n","English","en-US",{"_29":47,"_33":50,"_38":51},{"_31":48,"_33":34,"_35":49},"El Servidor MCP de Phoenix es una implementación del Protocolo de Contexto de Modelo para la plataforma Arize Phoenix. Proporciona una interfaz unificada para las funcionalidades de Phoenix.\n\nPuede utilizar Phoenix MCP Server para:\n\nAdministración de indicaciones: cree, enumere, actualice e itere en indicaciones Conjuntos de datos: explore conjuntos de datos y sintetice","[![Licencia](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://github.com/Arize-ai/phoenix/blob/main/js/packages/phoenix-mcp/LICENSE)\n\nEl Servidor MCP de Phoenix es una implementación del Protocolo de Contexto de Modelo para la plataforma Arize Phoenix. Proporciona una interfaz unificada para las funcionalidades de Phoenix.\n\nPuede utilizar Phoenix MCP Server para:\n\n* **Gestión de indicaciones** : crear, enumerar, actualizar e iterar indicaciones\n* **Conjuntos de datos** : explore conjuntos de datos y sintetice nuevos ejemplos\n* **Experimentos** : extraiga los resultados de los experimentos y visualícelos con la ayuda de un LLM\n\n¿No encuentras un caso práctico cubierto? `@arizeai/phoenix-mcp` es [de código abierto](https://github.com/Arize-ai/phoenix) ! Se agradecen problemas y solicitudes de relaciones públicas.\n\n## Instalación\n\nEste servidor MCP se puede utilizar mediante `npx` y se puede integrar directamente con clientes como Claude Desktop, Cursor y más.\n\n```json\n{\n \"mcpServers\": {\n \"phoenix\": {\n \"command\": \"npx\",\n \"args\": [\n \"-y\",\n \"@arizeai/phoenix-mcp@latest\",\n \"--baseUrl\",\n \"https://my-phoenix.com\",\n \"--apiKey\",\n \"your-api-key\"\n ]\n }\n }\n```\n\n## Desarrollo\n\n## Instalar\n\nEste paquete se administra a través de un espacio de trabajo pnpm.\n\n```sh\n// From the /js/ directory\npnpm install\npnpm build\n```\n\nEsto sólo es necesario repetirlo si cambian las dependencias o hay un cambio en el cliente phoenix.\n\n### Edificio\n\nPara construir el proyecto:\n\n```sh\npnpm build\n```\n\n### Modo de desarrollo\n\nPara ejecutar en modo de desarrollo:\n\n```bash\npnpm dev\n```\n\n### Depuración\n\nPuede crear y ejecutar el inspector MCP utilizando lo siguiente:\n\n```bash\npnpm inspect\n```\n\n## Variables de entorno\n\nDurante el desarrollo, el servidor requiere las siguientes variables de entorno:\n\n* `PHOENIX_API_KEY` : Su clave API de Phoenix\n* `PHOENIX_BASE_URL` : La URL base de Phoenix\n\nAsegúrese de configurarlos en un archivo `.env` . Consulte `.env.example` .\n\n# Licencia\n\nApache 2.0","Spanish","es-ES",{"_29":53,"_33":57,"_38":58},{"_31":54,"_33":55,"_35":56},"Phoenix MCPサーバーは、Arize Phoenixプラットフォーム向けのモデルコンテキストプロトコル（MCP）の実装です。Phoenixの機能への統一されたインターフェースを提供します。\n\nPhoenix MCP サーバーは次の用途に使用できます。\n\nプロンプト管理: プロンプトの作成、一覧表示、更新、反復処理データセット: データセットの探索、および","@arizeai/フェニックス-mcp","[![ライセンス](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://github.com/Arize-ai/phoenix/blob/main/js/packages/phoenix-mcp/LICENSE)\n\nPhoenix MCPサーバーは、Arize Phoenixプラットフォーム向けのモデルコンテキストプロトコル（MCP）の実装です。Phoenixの機能への統一されたインターフェースを提供します。\n\nPhoenix MCP サーバーは次の用途に使用できます。\n\n* **プロンプト管理**: プロンプトの作成、一覧表示、更新、反復処理\n* **データセット**: データセットを探索し、新しい例を合成する\n* **実験**: LLM の助けを借りて実験結果を引き出し、視覚化する\n\nユースケースが見つからないですか？ `@arizeai/phoenix-mcp`[オープンソース](https://github.com/Arize-ai/phoenix)です！問題や PR を歓迎します。\n\n## インストール\n\nこの MCP サーバーは`npx`を使用して使用でき、Claude Desktop、Cursor などのクライアントと直接統合できます。\n\n```json\n{\n \"mcpServers\": {\n \"phoenix\": {\n \"command\": \"npx\",\n \"args\": [\n \"-y\",\n \"@arizeai/phoenix-mcp@latest\",\n \"--baseUrl\",\n \"https://my-phoenix.com\",\n \"--apiKey\",\n \"your-api-key\"\n ]\n }\n }\n```\n\n## 発達\n\n## インストール\n\nこのパッケージは、pnpm ワークスペースを介して管理されます。\n\n```sh\n// From the /js/ directory\npnpm install\npnpm build\n```\n\n依存関係が変更された場合、または phoenix-client に変更があった場合にのみ、これを繰り返す必要があります。\n\n### 建物\n\nプロジェクトをビルドするには:\n\n```sh\npnpm build\n```\n\n### 開発モード\n\n開発モードで実行するには:\n\n```bash\npnpm dev\n```\n\n### デバッグ\n\n次のコマンドを使用して、MCP インスペクターをビルドして実行できます。\n\n```bash\npnpm inspect\n```\n\n## 環境変数\n\n開発時には、サーバーに次の環境変数が必要です。\n\n* `PHOENIX_API_KEY` : Phoenix APIキー\n* `PHOENIX_BASE_URL` : PhoenixのベースURL\n\nこれらは必ず`.env`ファイルで設定してください。.env.example `.env.example`参照してください。\n\n# ライセンス\n\nアパッチ 2.0","Japanese","ja-JP",{"_29":60,"_33":63,"_38":64},{"_31":61,"_33":34,"_35":62},"Phoenix MCP 서버는 Arize Phoenix 플랫폼을 위한 모델 컨텍스트 프로토콜(Model Context Protocol)을 구현한 서버입니다. Phoenix 기능에 대한 통합 인터페이스를 제공합니다.\n\nPhoenix MCP Server는 다음 용도로 사용할 수 있습니다.\n\n프롬프트 관리: 프롬프트를 생성, 나열, 업데이트 및 반복합니다. 데이터 세트: 데이터 세트를 탐색하고 구문을 작성합니다.","[![특허](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://github.com/Arize-ai/phoenix/blob/main/js/packages/phoenix-mcp/LICENSE)\n\nPhoenix MCP 서버는 Arize Phoenix 플랫폼을 위한 모델 컨텍스트 프로토콜(Model Context Protocol)을 구현한 서버입니다. Phoenix 기능에 대한 통합 인터페이스를 제공합니다.\n\nPhoenix MCP Server는 다음 용도로 사용할 수 있습니다.\n\n* **프롬프트 관리** : 프롬프트를 생성, 나열, 업데이트 및 반복합니다.\n* **데이터 세트** : 데이터 세트를 탐색하고 새로운 예를 종합합니다.\n* **실험** : LLM의 도움으로 실험 결과를 끌어와 시각화합니다.\n\n사용 사례가 보이지 않나요? `@arizeai/phoenix-mcp` [오픈 소스](https://github.com/Arize-ai/phoenix) 입니다! 이슈와 PR을 환영합니다.\n\n## 설치\n\n이 MCP 서버는 `npx` 사용하여 사용할 수 있으며 Claude Desktop, Cursor 등의 클라이언트와 직접 통합할 수 있습니다.\n\n지엑스피1\n\n## 개발\n\n## 설치하다\n\n이 패키지는 pnpm 작업 공간을 통해 관리됩니다.\n\n```sh\n// From the /js/ directory\npnpm install\npnpm build\n```\n\n종속성이 변경되거나 phoenix-client에 변경 사항이 있는 경우에만 이 작업을 반복하면 됩니다.\n\n### 건물\n\n프로젝트를 빌드하려면:\n\n```sh\npnpm build\n```\n\n### 개발 모드\n\n개발 모드에서 실행하려면:\n\n```bash\npnpm dev\n```\n\n### 디버깅\n\n다음을 사용하여 MCP 검사기를 빌드하고 실행할 수 있습니다.\n\n```bash\npnpm inspect\n```\n\n## 환경 변수\n\n개발 시 서버에는 다음과 같은 환경 변수가 필요합니다.\n\n* `PHOENIX_API_KEY` : Phoenix API 키\n* `PHOENIX_BASE_URL` : Phoenix의 기본 URL\n\n`.env` 파일에 설정해야 합니다. `.env.example` 참조하세요.\n\n# 특허\n\n아파치 2.0","Korean","ko-KR",{"_29":66,"_33":69,"_38":70},{"_31":67,"_33":34,"_35":68},"Phoenix MCP Server — это реализация Model Context Protocol для платформы Arize Phoenix. Он предоставляет унифицированный интерфейс для возможностей Phoenix.\n\nВы можете использовать Phoenix MCP Server для:\n\nУправление запросами: создание, перечисление, обновление и итерация запросов. Наборы данных: изучение наборов данных и их синтез.","[![Лицензия](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://github.com/Arize-ai/phoenix/blob/main/js/packages/phoenix-mcp/LICENSE)\n\nPhoenix MCP Server — это реализация Model Context Protocol для платформы Arize Phoenix. Он предоставляет унифицированный интерфейс для возможностей Phoenix.\n\nВы можете использовать Phoenix MCP Server для:\n\n* **Управление подсказками** : создание, перечисление, обновление и итерация подсказок.\n* **Наборы данных** : исследуйте наборы данных и синтезируйте новые примеры.\n* **Эксперименты** : извлечение результатов экспериментов и их визуализация с помощью LLM.\n\nНе видите рассмотренного варианта использования? `@arizeai/phoenix-mcp` — проект [с открытым исходным кодом](https://github.com/Arize-ai/phoenix) ! Вопросы и PR приветствуются.\n\n## Установка\n\nЭтот MCP-сервер можно использовать с помощью `npx` и напрямую интегрировать с такими клиентами, как Claude Desktop, Cursor и другими.\n\n```json\n{\n \"mcpServers\": {\n \"phoenix\": {\n \"command\": \"npx\",\n \"args\": [\n \"-y\",\n \"@arizeai/phoenix-mcp@latest\",\n \"--baseUrl\",\n \"https://my-phoenix.com\",\n \"--apiKey\",\n \"your-api-key\"\n ]\n }\n }\n```\n\n## Разработка\n\n## Установить\n\nУправление этим пакетом осуществляется через рабочее пространство pnpm.\n\n```sh\n// From the /js/ directory\npnpm install\npnpm build\n```\n\nЭто необходимо повторять только в случае изменения зависимостей или изменения клиента Phoenix.\n\n### Здание\n\nДля создания проекта:\n\n```sh\npnpm build\n```\n\n### Режим разработки\n\nДля запуска в режиме разработки:\n\n```bash\npnpm dev\n```\n\n### Отладка\n\nВы можете создать и запустить инспектор MCP, используя следующее:\n\n```bash\npnpm inspect\n```\n\n## Переменные среды\n\nПри разработке серверу требуются следующие переменные среды:\n\n* `PHOENIX_API_KEY` : Ваш ключ API Phoenix\n* `PHOENIX_BASE_URL` : базовый URL для Phoenix\n\nОбязательно задайте их в файле `.env` . См. `.env.example` .\n\n# Лицензия\n\nАпач 2.0","Russian","ru-RU",{"_29":72,"_33":75,"_38":76},{"_31":73,"_33":34,"_35":74},"Phoenix MCP 服务器是 Arize Phoenix 平台模型上下文协议 (MCP) 的实现，它为 Phoenix 的功能提供了统一的接口。\n\n您可以使用 Phoenix MCP 服务器进行以下操作：\n\n提示管理：创建、列出、更新和迭代提示数据集：探索数据集和合成","[![执照](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://github.com/Arize-ai/phoenix/blob/main/js/packages/phoenix-mcp/LICENSE)\n\nPhoenix MCP 服务器是 Arize Phoenix 平台模型上下文协议 (MCP) 的实现，它为 Phoenix 的功能提供了统一的接口。\n\n您可以使用 Phoenix MCP 服务器进行以下操作：\n\n* **提示管理**：创建、列出、更新和迭代提示\n* **数据集**：探索数据集并合成新示例\n* **实验**：提取实验结果，并在法学硕士的帮助下将其可视化\n\n没有找到涵盖的用例？ `@arizeai/phoenix-mcp`是[开源的](https://github.com/Arize-ai/phoenix)！欢迎提交问题和 PR。\n\n## 安装\n\n该 MCP 服务器可使用`npx`并且可直接与 Claude Desktop、Cursor 等客户端集成。\n\n```json\n{\n \"mcpServers\": {\n \"phoenix\": {\n \"command\": \"npx\",\n \"args\": [\n \"-y\",\n \"@arizeai/phoenix-mcp@latest\",\n \"--baseUrl\",\n \"https://my-phoenix.com\",\n \"--apiKey\",\n \"your-api-key\"\n ]\n }\n }\n```\n\n## 发展\n\n## 安装\n\n该包通过 pnpm 工作区进行管理。\n\n```sh\n// From the /js/ directory\npnpm install\npnpm build\n```\n\n仅当依赖项发生变化或 phoenix-client 发生变化时才需要重复此操作。\n\n### 建筑\n\n要构建项目：\n\n```sh\npnpm build\n```\n\n### 开发模式\n\n要在开发模式下运行：\n\n```bash\npnpm dev\n```\n\n### 调试\n\n您可以使用以下命令构建并运行 MCP 检查器：\n\n```bash\npnpm inspect\n```\n\n## 环境变量\n\n在开发时，服务器需要以下环境变量：\n\n* `PHOENIX_API_KEY` ：您的 Phoenix API 密钥\n* `PHOENIX_BASE_URL` ：Phoenix 的基本 URL\n\n确保将这些设置到`.env`文件中。请参阅`.env.example` 。\n\n# 执照\n\nApache 2.0","Chinese","zh-CN","githubUser","locale",{"_80":81,"_82":83,"_13":97,"_106":42,"_107":42,"_108":109,"_112":113,"_133":-5,"_16":134,"_135":136,"_137":138,"_33":34,"_156":125,"_157":158,"_161":-5,"_162":-5,"_163":-5,"_164":165,"_171":-5,"_145":121,"_172":-5,"_173":174,"_126":334,"_335":336},"addedAt","2025-04-10T14:26:47.249249171Z","argumentsJsonSchema",{"_84":85,"_94":95,"_89":96},"properties",{"_86":87,"_91":92},"PHOENIX_API_KEY",{"_31":88,"_89":90},"Your Phoenix API key","type","string","PHOENIX_BASE_URL",{"_31":93,"_89":90},"The base URL for Phoenix","required",[86,91],"object",[98,99,100,101,102,103,104,105],"author:official","category:monitoring","category:research-and-data","hosting:remote-capable","language:jupyter notebook","security_grade:a","quality_grade:a","license_grade:f","descriptionMarkdown","descriptionPlainText","githubProject",{"_35":43,"_110":111},"url","https://github.com/Arize-ai/phoenix/tree/main/js/packages/phoenix-mcp","githubRepository",{"_114":115,"_116":117,"_118":-5,"_119":120,"_33":121,"_122":123,"_128":129,"_130":-5,"_131":132},"defaultBranch","main","fullName","Arize-ai/phoenix","githubTreeId","language","Jupyter Notebook","phoenix","owner",{"_124":125,"_126":127},"login","Arize-ai","uid","XqRWwKUZK5","recentStargazers",83,"spdxLicense","stargazers",5722,"glamaJson",5275,"inspectable",true,"integrations",[139,149],{"_140":141,"_31":147,"_126":148},"brand",{"_142":143,"_33":144,"_145":146},"logoSvgPath","M24 0v24H0V0h24ZM10.933 15.89H6.84v5.52h4.198v-.93H7.955v-1.503h2.77v-.93h-2.77v-1.224h2.978v-.934Zm2.146 0h-1.084v5.52h1.035v-3.6l2.226 3.6h1.118v-5.52h-1.036v3.686l-2.259-3.687Zm5.117 0h-1.208l1.973 5.52h1.19l1.976-5.52h-1.182l-1.352 4.085-1.397-4.086ZM5.4 19.68H3.72v1.68H5.4v-1.68Z",".ENV","slug","dotenv","Enables environment variable configuration for development, allowing secure management of API keys and base URLs","i8vpqeiegu",{"_140":150,"_31":154,"_126":155},{"_142":151,"_33":152,"_145":153},"M12 .297c-6.63 0-12 5.373-12 12 0 5.303 3.438 9.8 8.205 11.385.6.113.82-.258.82-.577 0-.285-.01-1.04-.015-2.04-3.338.724-4.042-1.61-4.042-1.61C4.422 18.07 3.633 17.7 3.633 17.7c-1.087-.744.084-.729.084-.729 1.205.084 1.838 1.236 1.838 1.236 1.07 1.835 2.809 1.305 3.495.998.108-.776.417-1.305.76-1.605-2.665-.3-5.466-1.332-5.466-5.93 0-1.31.465-2.38 1.235-3.22-.135-.303-.54-1.523.105-3.176 0 0 1.005-.322 3.3 1.23.96-.267 1.98-.399 3-.405 1.02.006 2.04.138 3 .405 2.28-1.552 3.285-1.23 3.285-1.23.645 1.653.24 2.873.12 3.176.765.84 1.23 1.91 1.23 3.22 0 4.61-2.805 5.625-5.475 5.92.42.36.81 1.096.81 2.22 0 1.606-.015 2.896-.015 3.286 0 .315.21.69.825.57C20.565 22.092 24 17.592 24 12.297c0-6.627-5.373-12-12-12","GitHub","github","Provides open-source access to the Phoenix MCP implementation, allowing for contributions and customizations","tfkygckl5g","namespace","npmPackage",{"_33":34,"_159":160},"weeklyDownloads",154,"prompts","redditPostForeignId","resources","scores",{"_166":167,"_168":169,"_170":169},"license",0,"quality",100,"security","simpleIcon","supportedPlatforms","tools",[175,192,200,207,215,239,247,256,264,273,281,289,295,303,310],{"_33":176,"_31":177,"_178":179},"list-prompts","Get a list of all the prompts.\n\nPrompts (templates, prompt templates) are versioned templates for input messages to an LLM.\nEach prompt includes both the input messages, but also the model and invocation parameters\nto use when generating outputs.\n\nReturns a list of prompt objects with their IDs, names, and descriptions.\n\nExample usage: \n List all available prompts\n\nExpected return: \n Array of prompt objects with metadata. \n Example: [{\n \"name\": \"article-summarizer\",\n \"description\": \"Summarizes an article into concise bullet points\",\n \"source_prompt_id\": null,\n \"id\": \"promptid1234\"\n }]","inputSchema",{"_89":96,"_180":181,"_84":182,"_190":191},"$schema","http://json-schema.org/draft-07/schema#",{"_183":184},"limit",{"_89":185,"_186":169,"_187":169,"_188":189},"number","default","maximum","minimum",1,"additionalProperties",false,{"_33":193,"_31":194,"_178":195},"get-latest-prompt","Get the latest version of a prompt. Returns the prompt version with its template, model configuration, and invocation parameters.\n\nExample usage: \n Get the latest version of a prompt named 'article-summarizer'\n\nExpected return: \n Prompt version object with template and configuration. \n Example: {\n \"description\": \"Initial version\",\n \"model_provider\": \"OPENAI\",\n \"model_name\": \"gpt-3.5-turbo\",\n \"template\": {\n \"type\": \"chat\",\n \"messages\": [\n {\n \"role\": \"system\",\n \"content\": \"You are an expert summarizer. Create clear, concise bullet points highlighting the key information.\"\n },\n {\n \"role\": \"user\",\n \"content\": \"Please summarize the following {{topic}} article:\n\n{{article}}\"\n }\n ]\n },\n \"template_type\": \"CHAT\",\n \"template_format\": \"MUSTACHE\",\n \"invocation_parameters\": {\n \"type\": \"openai\",\n \"openai\": {}\n },\n \"id\": \"promptversionid1234\"\n }",{"_89":96,"_180":181,"_94":196,"_84":198,"_190":191},[197],"prompt_identifier",{"_197":199},{"_89":90},{"_33":201,"_31":202,"_178":203},"get-prompt-by-identifier","Get a prompt's latest version by its identifier (name or ID). Returns the prompt version with its template, model configuration, and invocation parameters.\n\nExample usage: \n Get the latest version of a prompt with name 'article-summarizer'\n\nExpected return: \n Prompt version object with template and configuration. \n Example: {\n \"description\": \"Initial version\",\n \"model_provider\": \"OPENAI\",\n \"model_name\": \"gpt-3.5-turbo\",\n \"template\": {\n \"type\": \"chat\",\n \"messages\": [\n {\n \"role\": \"system\",\n \"content\": \"You are an expert summarizer. Create clear, concise bullet points highlighting the key information.\"\n },\n {\n \"role\": \"user\",\n \"content\": \"Please summarize the following {{topic}} article:\n\n{{article}}\"\n }\n ]\n },\n \"template_type\": \"CHAT\",\n \"template_format\": \"MUSTACHE\",\n \"invocation_parameters\": {\n \"type\": \"openai\",\n \"openai\": {}\n },\n \"id\": \"promptversionid1234\"\n }",{"_89":96,"_180":181,"_94":204,"_84":205,"_190":191},[197],{"_197":206},{"_89":90},{"_33":208,"_31":209,"_178":210},"get-prompt-version","Get a specific version of a prompt using its version ID. Returns the prompt version with its template, model configuration, and invocation parameters.\n\nExample usage: \n Get a specific prompt version with ID 'promptversionid1234'\n\nExpected return: \n Prompt version object with template and configuration. \n Example: {\n \"description\": \"Initial version\",\n \"model_provider\": \"OPENAI\",\n \"model_name\": \"gpt-3.5-turbo\",\n \"template\": {\n \"type\": \"chat\",\n \"messages\": [\n {\n \"role\": \"system\",\n \"content\": \"You are an expert summarizer. Create clear, concise bullet points highlighting the key information.\"\n },\n {\n \"role\": \"user\",\n \"content\": \"Please summarize the following {{topic}} article:\n\n{{article}}\"\n }\n ]\n },\n \"template_type\": \"CHAT\",\n \"template_format\": \"MUSTACHE\",\n \"invocation_parameters\": {\n \"type\": \"openai\",\n \"openai\": {}\n },\n \"id\": \"promptversionid1234\"\n }",{"_89":96,"_180":181,"_94":211,"_84":213,"_190":191},[212],"prompt_version_id",{"_212":214},{"_89":90},{"_33":216,"_31":217,"_178":218},"upsert-prompt","Create or update a prompt with its template and configuration. Creates a new prompt and its initial version with specified model settings.\n\nExample usage: \n Create a new prompt named 'email_generator' with a template for generating emails\n\nExpected return: \n A confirmation message of successful prompt creation",{"_89":96,"_180":181,"_94":219,"_84":221,"_190":191},[33,220],"template",{"_33":222,"_220":223,"_224":225,"_31":227,"_228":229,"_231":232},{"_89":90},{"_89":90},"model_name",{"_89":90,"_186":226},"gpt-4",{"_89":90},"temperature",{"_89":185,"_186":230},0.7,"model_provider",{"_233":234,"_89":90,"_186":235},"enum",[235,236,237,238],"OPENAI","AZURE_OPENAI","ANTHROPIC","GOOGLE",{"_33":240,"_31":241,"_178":242},"list-prompt-versions","Get a list of all versions for a specific prompt. Returns versions with pagination support.\n\nExample usage: \n List all versions of a prompt named 'article-summarizer'\n\nExpected return: \n Array of prompt version objects with IDs and configuration. \n Example: [\n {\n \"description\": \"Initial version\",\n \"model_provider\": \"OPENAI\",\n \"model_name\": \"gpt-3.5-turbo\",\n \"template\": {\n \"type\": \"chat\",\n \"messages\": [\n {\n \"role\": \"system\",\n \"content\": \"You are an expert summarizer. Create clear, concise bullet points highlighting the key information.\"\n },\n {\n \"role\": \"user\",\n \"content\": \"Please summarize the following {{topic}} article:\n\n{{article}}\"\n }\n ]\n },\n \"template_type\": \"CHAT\",\n \"template_format\": \"MUSTACHE\",\n \"invocation_parameters\": {\n \"type\": \"openai\",\n \"openai\": {}\n },\n \"id\": \"promptversionid1234\"\n }\n ]",{"_89":96,"_180":181,"_94":243,"_84":244,"_190":191},[197],{"_183":245,"_197":246},{"_89":185,"_186":169,"_187":169,"_188":189},{"_89":90},{"_33":248,"_31":249,"_178":250},"get-prompt-version-by-tag","Get a prompt version by its tag name. Returns the prompt version with its template, model configuration, and invocation parameters.\n\nExample usage: \n Get the 'production' tagged version of prompt 'article-summarizer'\n\nExpected return: \n Prompt version object with template and configuration. \n Example: {\n \"description\": \"Initial version\",\n \"model_provider\": \"OPENAI\",\n \"model_name\": \"gpt-3.5-turbo\",\n \"template\": {\n \"type\": \"chat\",\n \"messages\": [\n {\n \"role\": \"system\",\n \"content\": \"You are an expert summarizer. Create clear, concise bullet points highlighting the key information.\"\n },\n {\n \"role\": \"user\",\n \"content\": \"Please summarize the following {{topic}} article:\n\n{{article}}\"\n }\n ]\n },\n \"template_type\": \"CHAT\",\n \"template_format\": \"MUSTACHE\",\n \"invocation_parameters\": {\n \"type\": \"openai\",\n \"openai\": {}\n },\n \"id\": \"promptversionid1234\"\n }",{"_89":96,"_180":181,"_94":251,"_84":253,"_190":191},[197,252],"tag_name",{"_252":254,"_197":255},{"_89":90},{"_89":90},{"_33":257,"_31":258,"_178":259},"list-prompt-version-tags","Get a list of all tags for a specific prompt version. Returns tag objects with pagination support.\n\nExample usage: \n List all tags associated with prompt version 'promptversionid1234'\n\nExpected return: \n Array of tag objects with names and IDs. \n Example: [\n {\n \"name\": \"staging\",\n \"description\": \"The version deployed to staging\",\n \"id\": \"promptversionid1234\"\n },\n {\n \"name\": \"development\",\n \"description\": \"The version deployed for development\",\n \"id\": \"promptversionid1234\"\n }\n ]",{"_89":96,"_180":181,"_94":260,"_84":261,"_190":191},[212],{"_183":262,"_212":263},{"_89":185,"_186":169,"_187":169,"_188":189},{"_89":90},{"_33":265,"_31":266,"_178":267},"add-prompt-version-tag","Add a tag to a specific prompt version. The operation returns no content on success (204 status code).\n\nExample usage: \n Tag prompt version 'promptversionid1234' with the name 'production'\n\nExpected return: \n Confirmation message of successful tag addition",{"_89":96,"_180":181,"_94":268,"_84":269,"_190":191},[212,33],{"_33":270,"_31":271,"_212":272},{"_89":90},{"_89":90},{"_89":90},{"_33":274,"_31":275,"_178":276},"list-experiments-for-dataset","Get a list of all the experiments run on a given dataset.\n\nExperiments are collections of experiment runs, each experiment run corresponds to a single \ndataset example. The dataset example is passed to an implied `task` which in turn \nproduces an output.\n\nExample usage:\n Show me all the experiments I've run on dataset RGF0YXNldDox\n\nExpected return:\n Array of experiment objects with metadata. \n Example: [\n {\n \"id\": \"experimentid1234\",\n \"dataset_id\": \"datasetid1234\",\n \"dataset_version_id\": \"datasetversionid1234\",\n \"repetitions\": 1,\n \"metadata\": {},\n \"project_name\": \"Experiment-abc123\",\n \"created_at\": \"YYYY-MM-DDTHH:mm:ssZ\",\n \"updated_at\": \"YYYY-MM-DDTHH:mm:ssZ\"\n }\n ]",{"_89":96,"_180":181,"_94":277,"_84":279,"_190":191},[278],"dataset_id",{"_278":280},{"_89":90},{"_33":282,"_31":283,"_178":284},"get-experiment-by-id","Get an experiment by its ID.\n\nThe tool returns experiment metadata in the first content block and a JSON object with the \nexperiment data in the second. The experiment data contains both the results of each \nexperiment run and the annotations made by an evaluator to score or label the results, \nfor example, comparing the output of an experiment run to the expected output from the \ndataset example.\n\nExample usage:\n Show me the experiment results for experiment RXhwZXJpbWVudDo4\n\nExpected return:\n Object containing experiment metadata and results.\n Example: {\n \"metadata\": {\n \"id\": \"experimentid1234\",\n \"dataset_id\": \"datasetid1234\",\n \"dataset_version_id\": \"datasetversionid1234\",\n \"repetitions\": 1,\n \"metadata\": {},\n \"project_name\": \"Experiment-abc123\",\n \"created_at\": \"YYYY-MM-DDTHH:mm:ssZ\",\n \"updated_at\": \"YYYY-MM-DDTHH:mm:ssZ\"\n },\n \"experimentResult\": [\n {\n \"example_id\": \"exampleid1234\",\n \"repetition_number\": 0,\n \"input\": \"Sample input text\",\n \"reference_output\": \"Expected output text\",\n \"output\": \"Actual output text\",\n \"error\": null,\n \"latency_ms\": 1000,\n \"start_time\": \"2025-03-20T12:00:00Z\",\n \"end_time\": \"2025-03-20T12:00:01Z\",\n \"trace_id\": \"trace-123\",\n \"prompt_token_count\": 10,\n \"completion_token_count\": 20,\n \"annotations\": [\n {\n \"name\": \"quality\",\n \"annotator_kind\": \"HUMAN\",\n \"label\": \"good\",\n \"score\": 0.9,\n \"explanation\": \"Output matches expected format\",\n \"trace_id\": \"trace-456\",\n \"error\": null,\n \"metadata\": {},\n \"start_time\": \"YYYY-MM-DDTHH:mm:ssZ\",\n \"end_time\": \"YYYY-MM-DDTHH:mm:ssZ\"\n }\n ]\n }\n ]\n }",{"_89":96,"_180":181,"_94":285,"_84":287,"_190":191},[286],"experiment_id",{"_286":288},{"_89":90},{"_33":290,"_31":291,"_178":292},"list-datasets","Get a list of all datasets.\n\nDatasets are collections of 'dataset examples' that each example includes an input, \n(expected) output, and optional metadata. They are primarily used as inputs for experiments.\n\nExample usage:\n Show me all available datasets\n\nExpected return:\n Array of dataset objects with metadata.\n Example: [\n {\n \"id\": \"RGF0YXNldDox\",\n \"name\": \"my-dataset\",\n \"description\": \"A dataset for testing\",\n \"metadata\": {},\n \"created_at\": \"2024-03-20T12:00:00Z\",\n \"updated_at\": \"2024-03-20T12:00:00Z\"\n }\n ]",{"_89":96,"_180":181,"_84":293,"_190":191},{"_183":294},{"_89":185,"_186":169,"_187":169,"_188":189},{"_33":296,"_31":297,"_178":298},"get-dataset-examples","Get examples from a dataset.\n\nDataset examples are an array of objects that each include an input, \n(expected) output, and optional metadata. These examples are typically used to represent \ninput to an application or model (e.g. prompt template variables, a code file, or image) \nand used to test or benchmark changes.\n\nExample usage:\n Show me all examples from dataset RGF0YXNldDox\n\nExpected return:\n Object containing dataset ID, version ID, and array of examples.\n Example: {\n \"dataset_id\": \"datasetid1234\",\n \"version_id\": \"datasetversionid1234\",\n \"examples\": [\n {\n \"id\": \"exampleid1234\",\n \"input\": {\n \"text\": \"Sample input text\"\n },\n \"output\": {\n \"text\": \"Expected output text\"\n },\n \"metadata\": {},\n \"updated_at\": \"YYYY-MM-DDTHH:mm:ssZ\"\n }\n ]\n }",{"_89":96,"_180":181,"_94":299,"_84":301,"_190":191},[300],"datasetId",{"_300":302},{"_89":90},{"_33":304,"_31":305,"_178":306},"get-dataset-experiments","List experiments run on a dataset.\n\nExample usage:\n Show me all experiments run on dataset RGF0YXNldDox\n\nExpected return:\n Array of experiment objects with metadata.\n Example: [\n {\n \"id\": \"experimentid1234\",\n \"dataset_id\": \"datasetid1234\",\n \"dataset_version_id\": \"datasetversionid1234\",\n \"repetitions\": 1,\n \"metadata\": {},\n \"project_name\": \"Experiment-abc123\",\n \"created_at\": \"YYYY-MM-DDTHH:mm:ssZ\",\n \"updated_at\": \"YYYY-MM-DDTHH:mm:ssZ\"\n }\n ]",{"_89":96,"_180":181,"_94":307,"_84":308,"_190":191},[300],{"_300":309},{"_89":90},{"_33":311,"_31":312,"_178":313},"add-dataset-examples","Add examples to an existing dataset.\n\nThis tool adds one or more examples to an existing dataset. Each example includes an input,\noutput, and metadata. The metadata will automatically include information indicating that\nthese examples were synthetically generated via MCP. When calling this tool, check existing\nexamples using the \"get-dataset-examples\" tool to ensure that you are not adding duplicate\nexamples and following existing patterns for how data should be structured.\n\nExample usage:\n Look at the analyze \"my-dataset\" and augment them with new examples to cover relevant edge cases\n\nExpected return:\n Confirmation of successful addition of examples to the dataset.\n Example: {\n \"dataset_name\": \"my-dataset\",\n \"message\": \"Successfully added examples to dataset\"\n 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\n \n \n \n \n \n \n \n \n \n Arize Phoenix MCP Server\n \n

\n
\n \n \n \n \n $\"Arize$ \n \n \n
\n Arize Phoenix MCP Server\n
\n

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