Translationx Mcp Server

Translationx Mcp Server

MCP Server for Translationx

Deep-Intelligent-Pharma

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TranslationX MCP Server (Python)

搭建Python虚拟环境

我们推荐通过uv构建虚拟环境来运行MCP server，关于`uv你可以在这里找到一些说明。

按照官方流程，你会安装Python包管理工具uv。除此之外，你也可以尝试其他方法（如Anaconda）来创建你的Python虚拟环境。

通过uv添加mcp依赖

uv add "mcp[cli]"

验证mcp依赖是否安装成功，执行如下命令

uv run mcp

当出现下图时代表安装成功

通过uv安装python，最低版本要求为3.13

uv python install 3.13

获取 MCP Server

前往TranslationX Mcp Server 官方开源仓库下载

配置本地项目

通过uv创建一个项目

uv init mcp_server_translation

将src文件夹拷贝到该目录下，通过如下命令测试mcp server是否正常运行

uv run --with mcp[cli] mcp run {YOUR_PATH}/src/main.py
# 如果是mac，需要加转义符
uv run --with mcp\[cli\] mcp run {YOUR_PATH}/src/main.py

如果没有报错则MCP Server启动成功

在Cursor中使用

打开Cursor配置，在MCP中添加MCP Server

在文件中添加如下内容后保存, TRANSLATIONX_TOKEN 可以在X-DOC中获取

{
  "mcpServers": {
    "translationx": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mcp[cli]",
        "mcp",
        "run",
        "{YOUR_PATH}/src/main.py"
      ],
      "env": {
        "token": "<YOUR_TRANSLATIONX_TOKEN>"
      }
    }
  }
}

回到配置，此时TranslationX MCP Server已经启用

测试

创建项目,并创建文件夹,然后文件到文件夹中，并提交翻译：

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