Mcp_server
About
Mcpserver is a MCP (Model Context Protocol) server configuration reference that demonstrates how to run MCP services using uv/uvx and connect clients via stdio, SSE, or streamable HTTP transports. It provides example configurations for multiple MCP tools such as math, weather…
Details
- Author
- hfhfn
- GitHub stars
- 5
- Downloads
- 118
- Categories
- Other
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- Supports uv/uvx for Python environment management
- Offers SSE and streamable HTTP URL modes
- Provides configuration examples for multiple MCP tools
- Supports stdio, SSE, and streamable HTTP transports
- Includes environment variable configuration for excel-mcp-server
- Uses Bearer token authentication for remote MCP services
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Mcp_serverCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Run the MCP service with uv run --with mcp[cli] mcp run path/to/mcp.py or uvx --with pillow --with mcp[cli] fastmcp run path/to/mcp.py. The service listens on port 8000 by default, offering SSE at /sse and streamable HTTP at /mcp. Configure your MCP client with one of the three transport modes (stdio, SSE, streamable HTTP) and the appropriate URL or command/args.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"mcp_server": {
"mcp-server-hfhfn": {
"command": "uv",
"args": [
"run",
"--with",
"mcp[cli]",
"mcp",
"run",
"path/to/mcp.py"
]
}
}
}
}McpServers
{
"mcp-server-hfhfn": {
"command": "uv",
"args": [
"run",
"--with",
"mcp[cli]",
"mcp",
"run",
"path/to/mcp.py"
]
}
}使用uv管理python环境
- uv启动mcp服务的python脚本
uv run --with mcp[cli] mcp run path/to/mcp.py
- uvx启动mcp服务的python脚本
uvx --with pillow --with mcp[cli] fastmcp run path/to/mcp.py
启动单个mcp服务 sse和streamable-http两种模式的URL路径
# sse 模式
http://127.0.0.1:8000/sse # 默认8000端口
http://host.docker.internal:8000/sse # docker容器内访问
streamable-http 模式
http://127.0.0.1:8000/mcp # 默认8000端口
http://host.docker.internal:8000/mcp # docker容器内访问
使用mcp工具的多种基本配置示例参考：
// 涉及3种模式：stdio，sse，streamable_http
{
// streamable_http模式
"mcpServers": {
"math": {
"transport": "streamable_http",
"url": "http://127.0.0.1:8000/mcp"
},
// sse模式
"weather": {
"transport": "sse",
"url": "http://127.0.0.1:8000/sse"
},
"12306-mcp": {
"type": "sse",
"url": "https://mcp.api-inference.modelscope.cn/sse/76ee2dbba8d74f"
},
"sequentialthinking": {
"headers": {
"Accept": "application/json, text/event-stream",
"Authorization": "Bearer 0e51a8cd-e77f-072ec3f3d161"
},
"url": "https://mcp.api-inference.modelscope.cn/sse/bb19488b5bc049"
},
// 本地服务 stdio模式
"quickchart-server": {
"isActive": true,
"command": "cmd",
"args": [
"/c",
"npx",
"-y",
"@gongrzhe/quickchart-mcp-server"
],
"name": "quickchart-server"
},
"excel-mcp-server": {
"isActive": true,
"command": "cmd",
"args": [
"/c",
"npx",
"--yes",
"@zhiweixu/excel-mcp-server"
],
"env": {
"LOG_PATH": "C:\\Users\\username\\Desktop\\temp",
"CACHE_MAX_AGE": "1",
"CACHE_CLEANUP_INTERVAL": "4",
"LOG_RETENTION_DAYS": "7",
"LOG_CLEANUP_INTERVAL": "24"
},
"name": "excel-mcp-server"
}
}
}
STDIO 模式启动说明
如果需要在客户端以 stdio 模式启动本项目：
1. 环境准备：
在项目根目录下运行以下命令，安装 MCP 命令行工具：
uv add "mcp[cli]"
2. 启动配置：
在配置客户端时，使用 uv 作为命令，并配合 --directory 参数指定项目路径。
- 命令: uv
- 参数: ["--directory", "/Users/hfhfn/charmProjects/mcp_server/", "run", "main.py"]
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