- Dev Log MCP Component
Dev Log MCP Component
Content
Dev Log MCP Component
A Model Context Protocol (MCP) component that manages a development log file. It provides endpoints for reading recent log entries and appending new entries with automatic timestamps.
Features
- Read last X entries from dev_log.md
- Append new entries with automatic timestamps and proper spacing
- Automatic dependency management
- Background process management with logging
Files
mcp_server.py- Flask implementation of dev log endpointsdev_rules.md- Development guidelines and logging format rulesdev_log.md- The log file containing timestamped entriesrequirements.txt- Python dependenciesstart_server.sh- Dev log service startup script with dependency installationstop_server.sh- Dev log service shutdown script
Installation & Usage
The service handles all dependency installation automatically. Just run:
./start_server.sh
This will:
- Check and install required system dependencies (Python3, pip)
- Set up a virtual environment
- Install Python dependencies
- Start the dev log service in the background
- Create a log file at devlog.log
To stop the service:
./stop_server.sh
API Endpoints
Read Log Entries
GET http://localhost:5002/read?lines=10
lines(optional): Number of recent entries to return (default: 10)- Returns: JSON array of log entries
Write Log Entry
POST http://localhost:5002/write
Content-Type: application/json
{
"entry": "Your log message here"
}
- Automatically prepends timestamp in format: "YYYY-MM-DD HH:MM:SS"
- Adds proper spacing between entries
- Returns: Success/error status
Monitoring
- Process ID is stored in
devlog.pid - Service output is logged to
devlog.log - Check service status:
ps -p $(cat devlog.pid)
Log Format
Each entry in dev_log.md follows this format:
## YYYY-MM-DD HH:MM:SS: Your log message here
Entries are separated by newlines for better readability. See dev_rules.md for detailed logging guidelines.
Recommend Servers
TraeBuild with Free GPT-4.1 & Claude 3.7. Fully MCP-Ready.
MiniMax MCPOfficial MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs.
CursorThe AI Code Editor
Tavily Mcp
MCP AdvisorMCP Advisor & Installation - Use the right MCP server for your needs
EdgeOne Pages MCPAn MCP service designed for deploying HTML content to EdgeOne Pages and obtaining an accessible public URL.
Playwright McpPlaywright MCP server
Howtocook Mcp基于Anduin2017 / HowToCook (程序员在家做饭指南)的mcp server,帮你推荐菜谱、规划膳食,解决“今天吃什么“的世纪难题;
Based on Anduin2017/HowToCook (Programmer's Guide to Cooking at Home), MCP Server helps you recommend recipes, plan meals, and solve the century old problem of "what to eat today"
Serper MCP ServerA Serper MCP Server
ChatWiseThe second fastest AI chatbot™
DeepChatYour AI Partner on Desktop
TimeA Model Context Protocol server that provides time and timezone conversion capabilities. This server enables LLMs to get current time information and perform timezone conversions using IANA timezone names, with automatic system timezone detection.
Baidu Map百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Jina AI MCP ToolsA Model Context Protocol (MCP) server that integrates with Jina AI Search Foundation APIs.
WindsurfThe new purpose-built IDE to harness magic
AiimagemultistyleA Model Context Protocol (MCP) server for image generation and manipulation using fal.ai's Stable Diffusion model.
BlenderBlenderMCP connects Blender to Claude AI through the Model Context Protocol (MCP), allowing Claude to directly interact with and control Blender. This integration enables prompt assisted 3D modeling, scene creation, and manipulation.
Visual Studio Code - Open Source ("Code - OSS")Visual Studio Code
Amap Maps高德地图官方 MCP Server
Zhipu Web SearchZhipu Web Search MCP Server is a search engine specifically designed for large models. It integrates four search engines, allowing users to flexibly compare and switch between them. Building upon the web crawling and ranking capabilities of traditional search engines, it enhances intent recognition capabilities, returning results more suitable for large model processing (such as webpage titles, URLs, summaries, site names, site icons, etc.). This helps AI applications achieve "dynamic knowledge acquisition" and "precise scenario adaptation" capabilities.
Context7Context7 MCP Server -- Up-to-date code documentation for LLMs and AI code editors