[{"_1":2,"_306":-5,"_307":-5},"loaderData",{"_3":4,"_29":30,"_31":32,"_252":253},"root",{"_5":6,"_14":15},"toasts",[7],{"_8":9,"_10":11,"_12":13},"uid","01972648-1cf3-70bf-9ee7-27a04bc769e9","title","This MCP server does not support inspection","type","error","visitor",{"_16":17,"_18":19},"viewportWidth",1280,"visitorSession",{"_20":21,"_23":24,"_25":-5,"_26":27,"_28":-5},"attributes",[22],"BOT","id",7058884,"membership","referenceId","01971406-43e3-74e8-b880-2f000258007a","userAccount","routes/_public/_layout",{},"routes/_public/mcp/servers/~namespace/~slug/_pages/_layout",{"_33":34,"_75":-5,"_76":35,"_36":77,"_170":171,"_251":128},"availableLocales",[35,47,54,61,68],{"_36":37,"_40":44,"_45":46},"mcpServer",{"_38":39,"_40":41,"_42":43},"description","A Python-based MCP server that allows Claude and other LLMs to execute arbitrary Python code directly through your desktop Claude app, enabling data scientists to connect LLMs to APIs and executable code.","name","Fused MCP Agents","readme","

\n Fused MCP Agents: Setting up MCP Servers for Data\n

\n\n

\n \n

\n\n

\n Documentation 🌪️ \n Read the announcement\n 🔥 \n \n Join Discord\n \n

\n\n\n[MCP servers](https://modelcontextprotocol.io/introduction) allow LLMs like Claude to make HTTP requests, connecting them to APIs & executable code. We built this repo for ourselves & anyone working with data to easily pass _any_ Python code directly to your own desktop Claude app. \n\n\n

\n \n \n \n \n

\n\n\n\nThis repo offers a simple step-by-step notebook workflow to setup [MCP Servers](https://modelcontextprotocol.io/introduction) with Claude's Desktop App, all in Python built on top of Fused [User Defined Functions](https://docs.fused.io/core-concepts/write/) (UDFs).\n\n![Demo once setup](https://fused-magic.s3.us-west-2.amazonaws.com/udf-mcp-repo/readme_asset/mcp_demo_fused_notebook_2.5x.gif)\n\n## Requirements\n- Python 3.11\n- Latest [Claude Desktop app](https://claude.ai/download) installed (macOS & Windows)\n\nIf you're on Linux, the desktop app isn't available so [we've made a simple client](#using-a-local-claude-client-without-claude-desktop-app) you can use to have it running locally too!\n\nYou do _not_ need a Fused account to do any of this! All of this will be running on your local machine.\n\n## Installation\n\n- Clone this repo in any local directory, and navigate to the repo: \n\n ```bash\n git clone https://github.com/fusedio/fused-mcp.git\n cd fused-mcp/\n ```\n\n- Install [`uv`](https://docs.astral.sh/uv/getting-started/installation/)\n if you don't have it:\n\n macOS / Linux:\n ```bash\n curl -LsSf https://astral.sh/uv/install.sh | sh\n ```\n\n Windows:\n ```\n powershell -ExecutionPolicy ByPass -c \"irm https://astral.sh/uv/install.ps1 | iex\"\n ```\n\n- Test out the client by asking for its info:\n\n ```bash\n uv run main.py -h\n ```\n\n- Start by following our getting-started notebook [`fused_mcp_agents.ipynb`](1.fused_mcp_agents.ipynb) in your favorite local IDE to get set up and then make your way to the more advanced notebook to [make your own Agents & functions](2.create_your_own_agents.ipynb)\n\n![Notebook](/img/Starting_notebook.gif)\n\n## Repository structure\n\nThis repo is build on top of [MCP Server](https://modelcontextprotocol.io/introduction) & [Fused UDFs](https://docs.fused.io/core-concepts/write/) which are Python functions that can be run from anywhere.\n\n## Support & Community\n\nFeel free to join our [Discord server](https://discord.com/invite/BxS5wMzdRk) if you want some help getting unblocked!\n\nHere are a few common steps to debug the setup:\n\n- Running `uv run main.py -h` should return something like this:\n\n![uv helper output function](/img/uv_run_helper_output.png)\n\n- You might need to pass global paths to some functions to the `Claude_Desktop_Config.json`. For example, by default we only pass `uv`:\n\n```json\n{\n \"mcpServers\": {\n \"qgis\": {\n \"command\": \"uv\",\n \"args\": [\"...\"]\n }\n\n }\n}\n```\n\nBut you might need to pass the full path to `uv`, which you can simply pass to `common.generate_local_mcp_config` in the notebook:\n\n```python\n# in fused_mcp_agents.ipynb\nimport shutil \n\ncommon.generate_local_mcp_config(\n config_path=PATH_TO_CLAUDE_CONFIG,\n agents_list = [\"get_current_time\"],\n repo_path= WORKING_DIR,\n uv_path=shutil.which('uv'),\n)\n```\n\nWhich would create a config like this:\n\n```json\n{\n \"mcpServers\": {\n \"qgis\": {\n \"command\": \"/Users//.local/bin/uv\",\n \"args\": [\"...\"]\n }\n\n }\n}\n```\n\n- If Claude runs without showing any connected tools, take a look at the [MCP Docs for troubleshooting the Claude Desktop setup](https://modelcontextprotocol.io/quickstart/server#claude-for-desktop-integration-issues)\n\n## Contribute\n\nFeel free to open PRs to add your own UDFs to `udfs/` so others can play around with them locally too!\n\n## Using a local Claude client (without Claude Desktop app)\n\nIf you are unable to install the Claude Desktop app (e.g., on Linux), we provide\na small example local client interface to use Claude with the MCP server configured\nin this repo:\n\nNOTE: You'll need an API key for Claude here as you won't use the Desktop App\n\n- Create an [Anthropic Console Account](https://console.anthropic.com/)\n- Create an [Anthropic API Key](https://console.anthropic.com/settings/keys)\n\n- Create a `.env`:\n ```bash\n touch .env\n ```\n\n- Add your key as `ANTHROPIC_API_KEY` inside the `.env`:\n\n ```\n # .env\n ANTHROPIC_API_KEY = \"your-key-here\"\n ```\n\n- Start the MCP server:\n\n ```bash\n uv run main.py --agent get_current_time\n ```\n\n- In another terminal session, start the local client, pointing to the address of the server:\n\n ```bash\n uv run client.py http://localhost:8080/sse\n ```\n","English","tag","en-US",{"_36":48,"_40":52,"_45":53},{"_38":49,"_40":50,"_42":51},"Un servidor MCP basado en Python que permite a Claude y otros LLM ejecutar código Python arbitrario directamente a través de su aplicación de escritorio Claude, lo que permite a los científicos de datos conectar LLM a API y código ejecutable.","Agentes MCP fusionados","[Los servidores MCP](https://modelcontextprotocol.io/introduction) permiten a los LLM como Claude realizar solicitudes HTTP, conectándolas a API y código ejecutable. Creamos este repositorio para nosotros y para cualquiera que trabaje con datos, para que puedas transferir fácilmente *cualquier* código Python directamente a tu aplicación de escritorio de Claude.\n\nEste repositorio ofrece un flujo de trabajo de cuaderno simple paso a paso para configurar [servidores MCP](https://modelcontextprotocol.io/introduction) con la aplicación de escritorio de Claude, todo en Python construido sobre [funciones definidas por el usuario](https://docs.fused.io/core-concepts/write/) fusionadas (UDF).\n\n![Demostración una vez configurada](https://fused-magic.s3.us-west-2.amazonaws.com/udf-mcp-repo/readme_asset/mcp_demo_fused_notebook_2.5x.gif)\n\n## Requisitos\n\n* Python 3.11\n* Última [aplicación de Claude Desktop](https://claude.ai/download) instalada (MacOS y Windows)\n\nSi estás en Linux, la aplicación de escritorio no está disponible, por eso [hemos creado un cliente simple](#using-a-local-claude-client-without-claude-desktop-app) que puedes usar para ejecutarla localmente también.\n\n¡ *No* necesitas una cuenta de Fused para hacer esto! Todo esto se ejecutará en tu equipo local.\n\n## Instalación\n\n* Clone este repositorio en cualquier directorio local y navegue hasta el repositorio:\n\n ```bash\n git clone https://github.com/fusedio/fused-mcp.git\n cd fused-mcp/\n ```\n\n* Instalar [`uv`](https://docs.astral.sh/uv/getting-started/installation/) si no lo tienes:\n\n macOS / Linux:\n\n ```bash\n curl -LsSf https://astral.sh/uv/install.sh | sh\n ```\n\n Ventanas:\n\n ```\n powershell -ExecutionPolicy ByPass -c \"irm https://astral.sh/uv/install.ps1 | iex\"\n ```\n\n* Pruebe el cliente solicitando su información:\n\n ```bash\n uv run main.py -h\n ```\n\n* Comience siguiendo nuestro cuaderno de introducción [`fused_mcp_agents.ipynb`](1.fused_mcp_agents.ipynb) en su IDE local favorito para configurarlo y luego avance hacia el cuaderno más avanzado para [crear sus propios agentes y funciones.](2.create_your_own_agents.ipynb)\n\n![Computadora portátil](/img/Starting_notebook.gif)\n\n## Estructura del repositorio\n\nEste repositorio está construido sobre [MCP Server](https://modelcontextprotocol.io/introduction) y [Fused UDF,](https://docs.fused.io/core-concepts/write/) que son funciones de Python que se pueden ejecutar desde cualquier lugar.\n\n## Soporte y comunidad\n\n¡No dudes en unirte a nuestro [servidor de Discord](https://discord.com/invite/BxS5wMzdRk) si quieres ayuda para desbloquearte!\n\nA continuación se muestran algunos pasos comunes para depurar la configuración:\n\n* Ejecutar `uv run main.py -h` debería devolver algo como esto:\n\n![función de salida auxiliar uv](/img/uv_run_helper_output.png)\n\n* Es posible que necesites pasar las rutas globales de algunas funciones a `Claude_Desktop_Config.json` . Por ejemplo, por defecto, solo pasamos `uv` :\n\n```json\n{\n \"mcpServers\": {\n \"qgis\": {\n \"command\": \"uv\",\n \"args\": [\"...\"]\n }\n\n }\n}\n```\n\nPero es posible que necesites pasar la ruta completa a `uv` , que puedes simplemente pasar a `common.generate_local_mcp_config` en el cuaderno:\n\n```python\n# in fused_mcp_agents.ipynb\nimport shutil \n\ncommon.generate_local_mcp_config(\n config_path=PATH_TO_CLAUDE_CONFIG,\n agents_list = [\"get_current_time\"],\n repo_path= WORKING_DIR,\n uv_path=shutil.which('uv'),\n)\n```\n\nLo que crearía una configuración como esta:\n\n```json\n{\n \"mcpServers\": {\n \"qgis\": {\n \"command\": \"/Users//.local/bin/uv\",\n \"args\": [\"...\"]\n }\n\n }\n}\n```\n\n* Si Claude se ejecuta sin mostrar ninguna herramienta conectada, consulte los [documentos de MCP para solucionar problemas de configuración de Claude Desktop.](https://modelcontextprotocol.io/quickstart/server#claude-for-desktop-integration-issues)\n\n## Contribuir\n\nSiéntete libre de abrir PR para agregar tus propios UDF a `udfs/` para que otros también puedan jugar con ellos localmente!\n\n## Usando un cliente Claude local (sin la aplicación Claude Desktop)\n\nSi no puede instalar la aplicación Claude Desktop (por ejemplo, en Linux), proporcionamos un pequeño ejemplo de interfaz de cliente local para usar Claude con el servidor MCP configurado en este repositorio:\n\nNOTA: Necesitarás una clave API para Claude aquí, ya que no usarás la aplicación de escritorio.\n\n* Crear una [cuenta de consola antrópica](https://console.anthropic.com/)\n\n* Crear una [clave API antrópica](https://console.anthropic.com/settings/keys)\n\n* Crear un `.env` :\n\n ```bash\n touch .env\n ```\n\n* Agregue su clave como `ANTHROPIC_API_KEY` dentro del `.env` :\n\n ```\n # .env\n ANTHROPIC_API_KEY = \"your-key-here\"\n ```\n\n* Inicie el servidor MCP:\n\n ```bash\n uv run main.py --agent get_current_time\n ```\n\n* En otra sesión de terminal, inicie el cliente local, apuntando a la dirección del servidor:\n\n ```bash\n uv run client.py http://localhost:8080/sse\n ```","Spanish","es-ES",{"_36":55,"_40":59,"_45":60},{"_38":56,"_40":57,"_42":58},"Python ベースの MCP サーバー。Claude や他の LLM がデスクトップの Claude アプリから直接任意の Python コードを実行できるようになり、データサイエンティストが LLM を API や実行可能コードに接続できるようになります。","融合MCPエージェント","[MCPサーバーは](https://modelcontextprotocol.io/introduction)、ClaudeのようなLLMがHTTPリクエストを送信し、APIや実行可能コードに接続できるようにします。このリポジトリは、私たち自身と、データを扱うすべてのユーザーが、Python*コード*を簡単にデスクトップのClaudeアプリに直接渡すことができるように構築しました。\n\nこのリポジトリは、Claude のデスクトップアプリを使用して[MCP サーバー](https://modelcontextprotocol.io/introduction)をセットアップするための、シンプルなステップバイステップのノートブックワークフローを提供します。すべて、Fused [User Defined Functions](https://docs.fused.io/core-concepts/write/) (UDF) 上に構築された Python で作成されています。\n\n![セットアップ後のデモ](https://fused-magic.s3.us-west-2.amazonaws.com/udf-mcp-repo/readme_asset/mcp_demo_fused_notebook_2.5x.gif)\n\n## 要件\n\n* Python 3.11\n* 最新の[Claudeデスクトップアプリ](https://claude.ai/download)がインストールされている（macOSおよびWindows）\n\nLinux をお使いの場合はデスクトップアプリは利用できないため、ローカルでも実行できる[シンプルなクライアントを作成しました](#using-a-local-claude-client-without-claude-desktop-app)。\n\nこれらを実行するのに Fused アカウントは必要あり*ません*。これらはすべてローカルマシン上で実行されます。\n\n## インストール\n\n* このリポジトリを任意のローカルディレクトリに複製し、リポジトリに移動します。\n\n ```bash\n git clone https://github.com/fusedio/fused-mcp.git\n cd fused-mcp/\n ```\n\n* [`uv`](https://docs.astral.sh/uv/getting-started/installation/)がインストールされていない場合はインストールします。\n\n macOS / Linux:\n\n ```bash\n curl -LsSf https://astral.sh/uv/install.sh | sh\n ```\n\n ウィンドウズ:\n\n ```\n powershell -ExecutionPolicy ByPass -c \"irm https://astral.sh/uv/install.ps1 | iex\"\n ```\n\n* 情報を要求してクライアントをテストします。\n\n ```bash\n uv run main.py -h\n ```\n\n* まずは、お気に入りのローカルIDEで、入門ノートブック[`fused_mcp_agents.ipynb`](1.fused_mcp_agents.ipynb)に従ってセットアップし、その後、より高度なノートブックに進んで、[独自のエージェントと関数を作成](2.create_your_own_agents.ipynb)してください。\n\n![ノート](/img/Starting_notebook.gif)\n\n## リポジトリ構造\n\nこのリポジトリは、どこからでも実行できる Python 関数である[MCP サーバー](https://modelcontextprotocol.io/introduction)と[Fused UDF](https://docs.fused.io/core-concepts/write/)上に構築されています。\n\n## サポートとコミュニティ\n\nブロック解除についてサポートが必要な場合は、お気軽に[Discord サーバー](https://discord.com/invite/BxS5wMzdRk)にご参加ください。\n\nセットアップをデバッグするための一般的な手順をいくつか示します。\n\n* `uv run main.py -h`実行すると、次のような結果が返されます。\n\n![UVヘルパー出力関数](/img/uv_run_helper_output.png)\n\n* `Claude_Desktop_Config.json`に、いくつかの関数へのグローバルパスを渡す必要があるかもしれません。例えば、デフォルトでは`uv`のみを渡します。\n\n```json\n{\n \"mcpServers\": {\n \"qgis\": {\n \"command\": \"uv\",\n \"args\": [\"...\"]\n }\n\n }\n}\n```\n\nただし、 `uv`へのフルパスを渡す必要がある場合があります。これは、ノートブックの`common.generate_local_mcp_config`に渡すだけで済みます。\n\n```python\n# in fused_mcp_agents.ipynb\nimport shutil \n\ncommon.generate_local_mcp_config(\n config_path=PATH_TO_CLAUDE_CONFIG,\n agents_list = [\"get_current_time\"],\n repo_path= WORKING_DIR,\n uv_path=shutil.which('uv'),\n)\n```\n\n次のような構成が作成されます。\n\n```json\n{\n \"mcpServers\": {\n \"qgis\": {\n \"command\": \"/Users//.local/bin/uv\",\n \"args\": [\"...\"]\n }\n\n }\n}\n```\n\n* Claude が接続されたツールを表示せずに実行される場合は、 [Claude デスクトップのセットアップのトラブルシューティングに関する MCP ドキュメント](https://modelcontextprotocol.io/quickstart/server#claude-for-desktop-integration-issues)を参照してください。\n\n## 貢献する\n\n自由に PR を開いて独自の UDF を`udfs/`に追加し、他の人もローカルで試せるようにしてください。\n\n## ローカルの Claude クライアントを使用する (Claude デスクトップアプリなし)\n\nClaude デスクトップアプリをインストールできない場合 (Linux など) は、このリポジトリで構成された MCP サーバーで Claude を使用するための小さなサンプルローカルクライアントインターフェイスが提供されています。\n\n注意: デスクトップアプリは使用しないので、ここではClaudeのAPIキーが必要になります。\n\n* [Anthropicコンソールアカウント](https://console.anthropic.com/)を作成する\n\n* [Anthropic APIキー](https://console.anthropic.com/settings/keys)を作成する\n\n* `.env`を作成します:\n\n ```bash\n touch .env\n ```\n\n* `.env`内に`ANTHROPIC_API_KEY`としてキーを追加します。\n\n ```\n # .env\n ANTHROPIC_API_KEY = \"your-key-here\"\n ```\n\n* MCP サーバーを起動します。\n\n ```bash\n uv run main.py --agent get_current_time\n ```\n\n* 別のターミナルセッションで、サーバーのアドレスを指定してローカルクライアントを起動します。\n\n ```bash\n uv run client.py http://localhost:8080/sse\n ```","Japanese","ja-JP",{"_36":62,"_40":66,"_45":67},{"_38":63,"_40":64,"_42":65},"Claude와 다른 LLM이 데스크톱 Claude 앱을 통해 임의의 Python 코드를 직접 실행할 수 있도록 하는 Python 기반 MCP 서버로, 데이터 과학자가 LLM을 API 및 실행 코드에 연결할 수 있습니다.","융합된 MCP 에이전트","[MCP 서버를](https://modelcontextprotocol.io/introduction) 사용하면 Claude와 같은 LLM이 HTTP 요청을 생성하여 API 및 실행 가능한 코드에 연결할 수 있습니다. 저희는 저 자신을 비롯하여 데이터 작업을 하는 모든 사람을 위해 *모든* Python 코드를 데스크톱 Claude 앱에 직접 쉽게 전달할 수 있도록 이 저장소를 구축했습니다.\n\n이 저장소는 퓨전 [사용자 정의 함수](https://docs.fused.io/core-concepts/write/) (UDF)를 기반으로 Python으로 구축된 클로드 데스크톱 앱으로 [MCP 서버를](https://modelcontextprotocol.io/introduction) 설정하는 간단한 단계별 노트북 워크플로를 제공합니다.\n\n![설정 후 데모](https://fused-magic.s3.us-west-2.amazonaws.com/udf-mcp-repo/readme_asset/mcp_demo_fused_notebook_2.5x.gif)\n\n## 요구 사항\n\n* 파이썬 3.11\n* 최신 [Claude Desktop 앱](https://claude.ai/download) 설치됨(macOS 및 Windows)\n\nLinux를 사용하는 경우 데스크톱 앱을 사용할 수 없으므로 로컬에서도 실행할 수 있는 [간단한 클라이언트를 만들었습니다](#using-a-local-claude-client-without-claude-desktop-app) !\n\n이 작업을 수행하는 데 Fused 계정은 필요 *하지 않습니다* ! 모든 작업은 로컬 컴퓨터에서 실행됩니다.\n\n## 설치\n\n* 로컬 디렉토리에 이 저장소를 복제하고 해당 저장소로 이동합니다.\n\n 지엑스피1\n\n* [`uv`](https://docs.astral.sh/uv/getting-started/installation/) 가 없다면 설치하세요:\n\n macOS / Linux:\n\n ```bash\n curl -LsSf https://astral.sh/uv/install.sh | sh\n ```\n\n 윈도우:\n\n ```\n powershell -ExecutionPolicy ByPass -c \"irm https://astral.sh/uv/install.ps1 | iex\"\n ```\n\n* 클라이언트의 정보를 요청하여 테스트해 보세요.\n\n ```bash\n uv run main.py -h\n ```\n\n* 좋아하는 로컬 IDE에서 시작하기 노트북 [`fused_mcp_agents.ipynb`](1.fused_mcp_agents.ipynb) 따라 설정을 시작한 다음 고급 노트북으로 이동하여 [나만의 에이전트 및 기능을 만드세요.](2.create_your_own_agents.ipynb)\n\n![공책](/img/Starting_notebook.gif)\n\n## 저장소 구조\n\n이 저장소는 어디서든 실행할 수 있는 Python 함수인 [MCP 서버](https://modelcontextprotocol.io/introduction) 와 [Fused UDF를](https://docs.fused.io/core-concepts/write/) 기반으로 구축되었습니다.\n\n## 지원 및 커뮤니티\n\n차단 해제에 도움이 필요하면 언제든지 저희 [Discord 서버](https://discord.com/invite/BxS5wMzdRk) 에 가입하세요!\n\n설정을 디버깅하는 몇 가지 일반적인 단계는 다음과 같습니다.\n\n* `uv run main.py -h` 실행하면 다음과 같은 결과가 반환됩니다.\n\n![uv 헬퍼 출력 함수](/img/uv_run_helper_output.png)\n\n* 일부 함수의 전역 경로를 `Claude_Desktop_Config.json` 파일에 전달해야 할 수도 있습니다. 예를 들어, 기본적으로 `uv` 만 전달합니다.\n\n```json\n{\n \"mcpServers\": {\n \"qgis\": {\n \"command\": \"uv\",\n \"args\": [\"...\"]\n }\n\n }\n}\n```\n\n하지만 `uv` 에 대한 전체 경로를 전달해야 할 수도 있는데, 이 경로는 노트북의 `common.generate_local_mcp_config` 에 간단히 전달할 수 있습니다.\n\n```python\n# in fused_mcp_agents.ipynb\nimport shutil \n\ncommon.generate_local_mcp_config(\n config_path=PATH_TO_CLAUDE_CONFIG,\n agents_list = [\"get_current_time\"],\n repo_path= WORKING_DIR,\n uv_path=shutil.which('uv'),\n)\n```\n\n그러면 다음과 같은 구성이 생성됩니다.\n\n```json\n{\n \"mcpServers\": {\n \"qgis\": {\n \"command\": \"/Users//.local/bin/uv\",\n \"args\": [\"...\"]\n }\n\n }\n}\n```\n\n* Claude가 연결된 도구를 표시하지 않고 실행되는 경우 [Claude Desktop 설정 문제 해결을 위한 MCP 문서를](https://modelcontextprotocol.io/quickstart/server#claude-for-desktop-integration-issues) 살펴보세요.\n\n## 기여하다\n\n자유롭게 PR을 열어 `udfs/` 에 자신의 UDF를 추가하면 다른 사람들도 로컬에서 이를 사용할 수 있습니다!\n\n## 로컬 Claude 클라이언트 사용(Claude Desktop 앱 없음)\n\nClaude Desktop 앱을 설치할 수 없는 경우(예: Linux에서) 이 저장소에 구성된 MCP 서버와 함께 Claude를 사용할 수 있는 작은 로컬 클라이언트 인터페이스 예를 제공합니다.\n\n참고: 데스크톱 앱을 사용하지 않으므로 여기에서는 Claude의 API 키가 필요합니다.\n\n* [Anthropic Console 계정](https://console.anthropic.com/) 만들기\n\n* [Anthropic API 키](https://console.anthropic.com/settings/keys) 생성\n\n* `.env` 생성합니다.\n\n ```bash\n touch .env\n ```\n\n* `.env` 내부에 `ANTHROPIC_API_KEY` 라는 키를 추가합니다.\n\n ```\n # .env\n ANTHROPIC_API_KEY = \"your-key-here\"\n ```\n\n* MCP 서버를 시작합니다.\n\n ```bash\n uv run main.py --agent get_current_time\n ```\n\n* 다른 터미널 세션에서 서버 주소를 가리키는 로컬 클라이언트를 시작합니다.\n\n ```bash\n uv run client.py http://localhost:8080/sse\n ```","Korean","ko-KR",{"_36":69,"_40":73,"_45":74},{"_38":70,"_40":71,"_42":72},"基于 Python 的 MCP 服务器允许 Claude 和其他 LLM 直接通过桌面 Claude 应用程序执行任意 Python 代码，使数据科学家能够将 LLM 连接到 API ��可执行代码。","融合 MCP 剂","[MCP 服务器](https://modelcontextprotocol.io/introduction)允许像 Claude 这样的 LLM 发出 HTTP 请求，并将其连接到 API 和可执行代码。我们为自己以及任何数据工作者构建了这个代码库，以便轻松地将*任何*Python 代码直接传输到您自己的桌面 Claude 应用程序中。\n\n这个 repo 提供了一个简单的分步笔记本工作流程，用于使用 Claude 的桌面应用程序设置[MCP 服务器](https://modelcontextprotocol.io/introduction)，所有这些都是在 Python 中基于融合[用户定义函数](https://docs.fused.io/core-concepts/write/)(UDF) 构建的。\n\n![设置后演示](https://fused-magic.s3.us-west-2.amazonaws.com/udf-mcp-repo/readme_asset/mcp_demo_fused_notebook_2.5x.gif)\n\n## 要求\n\n* Python 3.11\n* 安装了最新的[Claude Desktop 应用程序](https://claude.ai/download)（macOS 和 Windows）\n\n如果您使用的是 Linux，则桌面应用程序不可用，因此[我们制作了一个简单的客户端，](#using-a-local-claude-client-without-claude-desktop-app)您也可以使用它在本地运行它！\n\n您*无需*Fused 帐户即可执行任何操作！所有这些都将在您的本地计算机上运行。\n\n## 安装\n\n* 在任何本地目录中克隆此 repo，然后导航到该 repo：\n\n ```bash\n git clone https://github.com/fusedio/fused-mcp.git\n cd fused-mcp/\n ```\n\n* 如果你没有[`uv`](https://docs.astral.sh/uv/getting-started/installation/) ，请安装它：\n\n macOS / Linux：\n\n ```bash\n curl -LsSf https://astral.sh/uv/install.sh | sh\n ```\n\n 视窗：\n\n ```\n powershell -ExecutionPolicy ByPass -c \"irm https://astral.sh/uv/install.ps1 | iex\"\n ```\n\n* 通过询问客户端信息来测试客户端：\n\n ```bash\n uv run main.py -h\n ```\n\n* 首先在您最喜欢的本地 IDE 中按照我们的入门笔记本[`fused_mcp_agents.ipynb`](1.fused_mcp_agents.ipynb)进行设置，然后进入更高级的笔记本来[创建您自己的代理和功能](2.create_your_own_agents.ipynb)\n\n![笔记本](/img/Starting_notebook.gif)\n\n## 存储库结构\n\n这个 repo 建立在[MCP Server](https://modelcontextprotocol.io/introduction)和[Fused UDF](https://docs.fused.io/core-concepts/write/)之上，它们是可以从任何地方运行的 Python 函数。\n\n## 支持与社区\n\n如果您需要帮助解除封锁，请随时加入我们的[Discord 服务器](https://discord.com/invite/BxS5wMzdRk)！\n\n以下是调试设置的一些常见步骤：\n\n* 运行`uv run main.py -h`应该返回如下内容：\n\n![uv 辅助输出函数](/img/uv_run_helper_output.png)\n\n* 你可能需要将某些函数的全局路径传递给`Claude_Desktop_Config.json` 。例如，默认情况下我们只传递`uv` ：\n\n```json\n{\n \"mcpServers\": {\n \"qgis\": {\n \"command\": \"uv\",\n \"args\": [\"...\"]\n }\n\n }\n}\n```\n\n但是您可能需要将完整路径传递给`uv` ，您可以简单地将其传递给笔记本中的`common.generate_local_mcp_config` ：\n\n```python\n# in fused_mcp_agents.ipynb\nimport shutil \n\ncommon.generate_local_mcp_config(\n config_path=PATH_TO_CLAUDE_CONFIG,\n agents_list = [\"get_current_time\"],\n repo_path= WORKING_DIR,\n uv_path=shutil.which('uv'),\n)\n```\n\n这将创建如下配置：\n\n```json\n{\n \"mcpServers\": {\n \"qgis\": {\n \"command\": \"/Users//.local/bin/uv\",\n \"args\": [\"...\"]\n }\n\n }\n}\n```\n\n* 如果 Claude 运行时没有显示任何连接的工具，请查看[MCP 文档以排除 Claude Desktop 设置故障](https://modelcontextprotocol.io/quickstart/server#claude-for-desktop-integration-issues)\n\n## 贡献\n\n请随意打开 PR 将您自己的 UDF 添加到`udfs/`以便其他人也可以在本地使用它们！\n\n## 使用本地 Claude 客户端（无需 Claude 桌面应用程序）\n\n如果您无法安装 Claude 桌面应用程序（例如在 Linux 上），我们提供了一个小型示例本地客户端界面，以便将 Claude 与此 repo 中配置的 MCP 服务器一起使用：\n\n注意：由于您不会使用桌面应用程序，因此您需要 Claude 的 API 密钥\n\n* 创建[Anthropic Console 帐户](https://console.anthropic.com/)\n\n* 创建[Anthropic API 密钥](https://console.anthropic.com/settings/keys)\n\n* 创建一个`.env` ：\n\n ```bash\n touch .env\n ```\n\n* 在`.env`中将您的密钥添加为`ANTHROPIC_API_KEY` ：\n\n ```\n # .env\n ANTHROPIC_API_KEY = \"your-key-here\"\n ```\n\n* 启动 MCP 服务器：\n\n ```bash\n uv run main.py --agent get_current_time\n ```\n\n* 在另一个终端会话中，启动本地客户端，指向服务器的地址：\n\n ```bash\n uv run client.py http://localhost:8080/sse\n ```","Chinese","zh-CN","githubUser","locale",{"_78":79,"_80":81,"_20":87,"_96":39,"_97":39,"_98":99,"_102":103,"_125":-5,"_23":126,"_127":128,"_129":130,"_40":41,"_148":116,"_149":-5,"_150":-5,"_151":152,"_153":-5,"_154":155,"_160":-5,"_137":112,"_161":162,"_166":-5,"_8":167,"_168":169},"addedAt","2025-03-18T17:00:42.997997108Z","argumentsJsonSchema",{"_82":83,"_84":85,"_12":86},"properties",{},"required",[],"object",[88,89,90,91,92,93,94,95],"author:official","category:code-execution","category:developer-tools","category:agent-orchestration","environment:local","hosting:local-only","language:jupyter 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