fetch-log-mcp-server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@fetch-log-mcp-server fetch logs from 10.0.0.5"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Fetch Log MCP Server
一个用于获取远端日志的 MCP (Model Context Protocol) 服务器。
功能特性
支持从指定 IP 地址获取日志内容
可配置端口号和日志路径
使用 TypeScript 开发,类型安全
简单易用的 API 接口
Related MCP server: journald-mcp-server
安装和运行
方法一:全局安装(推荐)
# 全局安装
npm install -g .
# 查看帮助
fetch-log-mcp-server --help
# 查看版本
fetch-log-mcp-server --version
# 启动服务器
fetch-log-mcp-server方法二:本地开发
# 1. 安装依赖
npm install
# 2. 构建项目
npm run build
# 3. 运行服务器
npm start
# 4. 开发模式
npm run dev使用方法
命令行选项
--help, -h: 显示帮助信息--version, -v: 显示版本信息
MCP 工具参数
ip(必需): 目标服务器的 IP 地址port(可选): 目标服务器的端口号,默认为 28668path(可选): 日志路径,默认为/logs
示例
1. 启动 MCP 服务器
fetch-log-mcp-server2. 通过 MCP 客户端调用工具
{
"name": "fetch_logs",
"arguments": {
"ip": "192.168.1.100",
"port": 28668,
"path": "/logs"
}
}这将执行 curl -XGET "http://192.168.1.100:28668/logs" 来获取日志内容。
3. 配置文件示例 (mcp.json)
{
"mcpServers": {
"fetch-log-server": {
"command": "fetch-log-mcp-server"
}
}
}项目结构
fetch-log-mcp-server/
├── src/
│ └── index.ts # 主服务器文件
├── dist/ # 编译输出目录
├── package.json # 项目配置
├── tsconfig.json # TypeScript 配置
└── README.md # 项目说明技术栈
TypeScript
@modelcontextprotocol/sdk
axios (用于 HTTP 请求)
错误处理
服务器包含完善的错误处理机制:
网络请求超时(30秒)
连接错误处理
参数验证
许可证
MIT
Available Tools
1 toolfetch_logsB
从指定的IP地址获取日志内容
Inputs: ip (required), path, port.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 1 tool
With only a single tool, there is no possible ambiguity or overlap. The tool's purpose is uniquely defined by its name and description.
The sole tool name 'fetch_logs' follows a clean verb_noun pattern, matching the server name 'fetch-log-mcp-server'. Even with one tool, the naming is predictable and consistent.
The server has exactly one tool, which falls below the typical well-scoped range of 3-15 tools. It is narrowly focused on fetching logs, so it feels thin but not completely unreasonable for a single-purpose utility.
The tool surface is severely limited, offering only 'fetch_logs' with no supporting operations like listing available log sources, filtering by time or type, or handling failures. For a logging domain, this leaves significant gaps that could hinder an agent's workflow.
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