| Name | baiyx-mcp-server-dispatch JSON |
| Version |
0.1.7
JSON |
| download |
| home_page | None |
| Summary | A Model Context Protocol server providing dispatch functionality |
| upload_time | 2025-04-21 07:39:47 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | MIT |
| keywords |
dispatch
llm
mcp
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# MCP Excel Server
一个基于 Model Context Protocol (MCP) 的 Excel 处理服务器，提供以下功能：
1. 获取 Excel 工作簿信息
- 读取所有工作表名称
- 获取每个工作表的表头
- 获取数据范围信息
2. 读取 Excel 数据
- 支持按范围读取数据
- 支持读取公式
3. 写入 Excel 数据
- 支持按范围写入数据
- 支持写入公式
## 安装
```bash
pip install baiyx-mcp-server-excel
```
## 使用方法
启动服务器：
```bash
baiyx-mcp-server-excel
```
## 功能说明
### 1. 获取工作簿信息
```python
get_workbook_info(file_path: str) -> WorkbookInfo
```
返回工作簿中所有工作表的信息，包括表名、表头和数据范围。
### 2. 读取数据
```python
read_sheet_data(file_path: str, sheet_name: str, range: Optional[str] = None) -> ExcelData
```
从指定工作表读取数据，可以指定读取范围（例如："A1:C10"）。
### 3. 读取公式
```python
read_sheet_formula(file_path: str, sheet_name: str, range: Optional[str] = None) -> ExcelFormula
```
从指定工作表读取公式，可以指定读取范围。
### 4. 写入数据
```python
write_sheet_data(file_path: str, sheet_name: str, range: str, data: List[List[Any]]) -> bool
```
向指定工作表写入数据，需要指定写入范围。
### 5. 写入公式
```python
write_sheet_formula(file_path: str, sheet_name: str, range: str, formulas: List[str]) -> bool
```
向指定工作表写入公式，需要指定写入范围。
## 示例
```python
# 获取工作簿信息
workbook_info = get_workbook_info("example.xlsx")
print(f"Found {len(workbook_info.sheets)} sheets")
# 读取数据
data = read_sheet_data("example.xlsx", "Sheet1", "A1:C10")
print(f"Read {len(data.data)} rows")
# 写入数据
success = write_sheet_data("example.xlsx", "Sheet1", "A1", [[1, 2, 3], [4, 5, 6]])
print(f"Write {'successful' if success else 'failed'}")
```
## 依赖
- Python >= 3.10
- mcp >= 1.6.0
- pandas >= 2.0.0
- openpyxl >= 3.1.2
## 许可证
MIT
# MCP 派车服务
这是一个基于 MCP (Model Context Protocol) 的派车服务，提供批量外部派车功能。
## 功能特点
- 支持批量外部派车操作
- 支持多组订单号、供应商和指派类型
- 自动处理错误和异常情况
- 提供详细的处理结果反馈
## 安装
```bash
pip install baiyx-mcp-server-dispatch
```
## 使用方法
1. 启动服务：
```bash
baiyx-mcp-server-dispatch
```
2. 调用示例：
```python
from mcp.client import Client
# 创建MCP客户端
client = Client()
# 准备派车数据
dispatch_groups = [
{
"order_numbers": ["订单1", "订单2"],
"supplier_name": "供应商A",
"dispatch_type": "提货"
},
{
"order_numbers": ["订单3"],
"supplier_name": "供应商B",
"dispatch_type": "送货"
}
]
# 调用批量派车功能
result = await client.batch_external_dispatch(dispatch_groups=dispatch_groups)
print(result)
```
## API说明
### batch_external_dispatch
批量处理外部派车请求。
参数：
- dispatch_groups: List[Dict] - 派车组列表，每个组包含：
- order_numbers: List[str] - 订单号列表
- supplier_name: str - 供应商名称
- dispatch_type: str - 指派类型（"提货"/"送货"/"干线"）
返回值：
```python
{
"success": bool, # 是否成功
"message": str, # 处理结果消息
"success_count": int, # 成功处理的组数
"failed_groups": List[Dict] # 失败的组及原因
}
```
## 配置说明
服务使用以下环境变量进行配置：
- API_TOKEN: API访问令牌
- BASE_URL: API基础URL
- SPACE_ID: 空间ID
## 开发
1. 克隆代码：
```bash
git clone https://github.com/yourusername/baiyx-mcp-server-dispatch.git
```
2. 安装依赖：
```bash
pip install -e ".[dev]"
```
3. 运行测试：
```bash
pytest
```
## 许可证
MIT
## 作者
baiyx (baiyx@example.com)
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"description": "# MCP Excel Server\n\n\u4e00\u4e2a\u57fa\u4e8e Model Context Protocol (MCP) \u7684 Excel \u5904\u7406\u670d\u52a1\u5668\uff0c\u63d0\u4f9b\u4ee5\u4e0b\u529f\u80fd\uff1a\n\n1. \u83b7\u53d6 Excel \u5de5\u4f5c\u7c3f\u4fe1\u606f\n - \u8bfb\u53d6\u6240\u6709\u5de5\u4f5c\u8868\u540d\u79f0\n - \u83b7\u53d6\u6bcf\u4e2a\u5de5\u4f5c\u8868\u7684\u8868\u5934\n - \u83b7\u53d6\u6570\u636e\u8303\u56f4\u4fe1\u606f\n\n2. \u8bfb\u53d6 Excel \u6570\u636e\n - \u652f\u6301\u6309\u8303\u56f4\u8bfb\u53d6\u6570\u636e\n - \u652f\u6301\u8bfb\u53d6\u516c\u5f0f\n\n3. \u5199\u5165 Excel \u6570\u636e\n - \u652f\u6301\u6309\u8303\u56f4\u5199\u5165\u6570\u636e\n - \u652f\u6301\u5199\u5165\u516c\u5f0f\n\n## \u5b89\u88c5\n\n```bash\npip install baiyx-mcp-server-excel\n```\n\n## \u4f7f\u7528\u65b9\u6cd5\n\n\u542f\u52a8\u670d\u52a1\u5668\uff1a\n\n```bash\nbaiyx-mcp-server-excel\n```\n\n## \u529f\u80fd\u8bf4\u660e\n\n### 1. \u83b7\u53d6\u5de5\u4f5c\u7c3f\u4fe1\u606f\n\n```python\nget_workbook_info(file_path: str) -> WorkbookInfo\n```\n\n\u8fd4\u56de\u5de5\u4f5c\u7c3f\u4e2d\u6240\u6709\u5de5\u4f5c\u8868\u7684\u4fe1\u606f\uff0c\u5305\u62ec\u8868\u540d\u3001\u8868\u5934\u548c\u6570\u636e\u8303\u56f4\u3002\n\n### 2. \u8bfb\u53d6\u6570\u636e\n\n```python\nread_sheet_data(file_path: str, sheet_name: str, range: Optional[str] = None) -> ExcelData\n```\n\n\u4ece\u6307\u5b9a\u5de5\u4f5c\u8868\u8bfb\u53d6\u6570\u636e\uff0c\u53ef\u4ee5\u6307\u5b9a\u8bfb\u53d6\u8303\u56f4\uff08\u4f8b\u5982\uff1a\"A1:C10\"\uff09\u3002\n\n### 3. \u8bfb\u53d6\u516c\u5f0f\n\n```python\nread_sheet_formula(file_path: str, sheet_name: str, range: Optional[str] = None) -> ExcelFormula\n```\n\n\u4ece\u6307\u5b9a\u5de5\u4f5c\u8868\u8bfb\u53d6\u516c\u5f0f\uff0c\u53ef\u4ee5\u6307\u5b9a\u8bfb\u53d6\u8303\u56f4\u3002\n\n### 4. \u5199\u5165\u6570\u636e\n\n```python\nwrite_sheet_data(file_path: str, sheet_name: str, range: str, data: List[List[Any]]) -> bool\n```\n\n\u5411\u6307\u5b9a\u5de5\u4f5c\u8868\u5199\u5165\u6570\u636e\uff0c\u9700\u8981\u6307\u5b9a\u5199\u5165\u8303\u56f4\u3002\n\n### 5. \u5199\u5165\u516c\u5f0f\n\n```python\nwrite_sheet_formula(file_path: str, sheet_name: str, range: str, formulas: List[str]) -> bool\n```\n\n\u5411\u6307\u5b9a\u5de5\u4f5c\u8868\u5199\u5165\u516c\u5f0f\uff0c\u9700\u8981\u6307\u5b9a\u5199\u5165\u8303\u56f4\u3002\n\n## \u793a\u4f8b\n\n```python\n# \u83b7\u53d6\u5de5\u4f5c\u7c3f\u4fe1\u606f\nworkbook_info = get_workbook_info(\"example.xlsx\")\nprint(f\"Found {len(workbook_info.sheets)} sheets\")\n\n# \u8bfb\u53d6\u6570\u636e\ndata = read_sheet_data(\"example.xlsx\", \"Sheet1\", \"A1:C10\")\nprint(f\"Read {len(data.data)} rows\")\n\n# \u5199\u5165\u6570\u636e\nsuccess = write_sheet_data(\"example.xlsx\", \"Sheet1\", \"A1\", [[1, 2, 3], [4, 5, 6]])\nprint(f\"Write {'successful' if success else 'failed'}\")\n```\n\n## \u4f9d\u8d56\n\n- Python >= 3.10\n- mcp >= 1.6.0\n- pandas >= 2.0.0\n- openpyxl >= 3.1.2\n\n## \u8bb8\u53ef\u8bc1\n\nMIT\n\n# MCP \u6d3e\u8f66\u670d\u52a1\n\n\u8fd9\u662f\u4e00\u4e2a\u57fa\u4e8e MCP (Model Context Protocol) \u7684\u6d3e\u8f66\u670d\u52a1\uff0c\u63d0\u4f9b\u6279\u91cf\u5916\u90e8\u6d3e\u8f66\u529f\u80fd\u3002\n\n## \u529f\u80fd\u7279\u70b9\n\n- \u652f\u6301\u6279\u91cf\u5916\u90e8\u6d3e\u8f66\u64cd\u4f5c\n- \u652f\u6301\u591a\u7ec4\u8ba2\u5355\u53f7\u3001\u4f9b\u5e94\u5546\u548c\u6307\u6d3e\u7c7b\u578b\n- \u81ea\u52a8\u5904\u7406\u9519\u8bef\u548c\u5f02\u5e38\u60c5\u51b5\n- \u63d0\u4f9b\u8be6\u7ec6\u7684\u5904\u7406\u7ed3\u679c\u53cd\u9988\n\n## \u5b89\u88c5\n\n```bash\npip install baiyx-mcp-server-dispatch\n```\n\n## \u4f7f\u7528\u65b9\u6cd5\n\n1. \u542f\u52a8\u670d\u52a1\uff1a\n\n```bash\nbaiyx-mcp-server-dispatch\n```\n\n2. \u8c03\u7528\u793a\u4f8b\uff1a\n\n```python\nfrom mcp.client import Client\n\n# \u521b\u5efaMCP\u5ba2\u6237\u7aef\nclient = Client()\n\n# \u51c6\u5907\u6d3e\u8f66\u6570\u636e\ndispatch_groups = [\n {\n \"order_numbers\": [\"\u8ba2\u53551\", \"\u8ba2\u53552\"],\n \"supplier_name\": \"\u4f9b\u5e94\u5546A\",\n \"dispatch_type\": \"\u63d0\u8d27\"\n },\n {\n \"order_numbers\": [\"\u8ba2\u53553\"],\n \"supplier_name\": \"\u4f9b\u5e94\u5546B\",\n \"dispatch_type\": \"\u9001\u8d27\"\n }\n]\n\n# \u8c03\u7528\u6279\u91cf\u6d3e\u8f66\u529f\u80fd\nresult = await client.batch_external_dispatch(dispatch_groups=dispatch_groups)\nprint(result)\n```\n\n## API\u8bf4\u660e\n\n### batch_external_dispatch\n\n\u6279\u91cf\u5904\u7406\u5916\u90e8\u6d3e\u8f66\u8bf7\u6c42\u3002\n\n\u53c2\u6570\uff1a\n- dispatch_groups: List[Dict] - \u6d3e\u8f66\u7ec4\u5217\u8868\uff0c\u6bcf\u4e2a\u7ec4\u5305\u542b\uff1a\n - order_numbers: List[str] - \u8ba2\u5355\u53f7\u5217\u8868\n - supplier_name: str - \u4f9b\u5e94\u5546\u540d\u79f0\n - dispatch_type: str - \u6307\u6d3e\u7c7b\u578b\uff08\"\u63d0\u8d27\"/\"\u9001\u8d27\"/\"\u5e72\u7ebf\"\uff09\n\n\u8fd4\u56de\u503c\uff1a\n```python\n{\n \"success\": bool, # \u662f\u5426\u6210\u529f\n \"message\": str, # \u5904\u7406\u7ed3\u679c\u6d88\u606f\n \"success_count\": int, # \u6210\u529f\u5904\u7406\u7684\u7ec4\u6570\n \"failed_groups\": List[Dict] # \u5931\u8d25\u7684\u7ec4\u53ca\u539f\u56e0\n}\n```\n\n## \u914d\u7f6e\u8bf4\u660e\n\n\u670d\u52a1\u4f7f\u7528\u4ee5\u4e0b\u73af\u5883\u53d8\u91cf\u8fdb\u884c\u914d\u7f6e\uff1a\n\n- API_TOKEN: API\u8bbf\u95ee\u4ee4\u724c\n- BASE_URL: API\u57fa\u7840URL\n- SPACE_ID: \u7a7a\u95f4ID\n\n## \u5f00\u53d1\n\n1. \u514b\u9686\u4ee3\u7801\uff1a\n\n```bash\ngit clone https://github.com/yourusername/baiyx-mcp-server-dispatch.git\n```\n\n2. \u5b89\u88c5\u4f9d\u8d56\uff1a\n\n```bash\npip install -e \".[dev]\"\n```\n\n3. \u8fd0\u884c\u6d4b\u8bd5\uff1a\n\n```bash\npytest\n```\n\n## \u8bb8\u53ef\u8bc1\n\nMIT\n\n## \u4f5c\u8005\n\nbaiyx (baiyx@example.com)\n",
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