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MCP Server Baidu Maps Enhanced - HTTP call Baidu Map API for MCP

Project description

Baidu Map MCP Server (Python)

🚀 快速启动(推荐)

使用 UVX 一键启动

uvx bach-baidu-maps

在 Cursor/Cherry Studio 中配置

{
  "mcpServers": {
    "baidu-maps": {
      "command": "uvx",
      "args": ["bach-baidu-maps"],
      "env": {
        "BAIDU_MAPS_API_KEY": "<YOUR_API_KEY>"
      }
    }
  }
}

包地址: https://pypi.org/project/bach-baidu-maps/


传统方式: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 3.11

uv python install 3.11

获取 MCP Server

前往百度地图 MCP Server 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_baidu_maps

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

{
  "mcpServers": {
    "baidu-map": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mcp[cli]",
        "mcp",
        "run",
        "{YOUR_PATH}/mcp_server_baidu_maps/map.py"
      ],
      "env": {
        "BAIDU_MAPS_API_KEY": "<YOUR_API_KEY>"
      }
    }
  }
}

回到配置,此时百度 MCP Server 已经启用

测试

行程规划:

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