Log Reader MCP Server

🚀 Log Reader Mcp

🚀 Stop wasting time copy-pasting logs! 🧠 Let Cursor's AI instantly access, search, and explain your logs — no more manual work, just answers.

📚 Table of Contents

• Why Log Reader Mcp?
• Installation
  • Automatic (recommended)
  • Manual
• Who is it for?
• MCP Configuration
• Example Prompts for Cursor
• CLI Usage
• Log Format (JSON per line)
• Developer Guide
• Key Advantages
• FAQ
• Getting Help
• Contributing
• License
• Cursor Rule (Workflow)

✨ Why Log Reader Mcp?

• 🤖 AI-powered log access: Give your AI assistant (Cursor, etc.) direct, on-demand access to your app logs.
• 🧠 Smarter debugging: Let the AI analyze, summarize, and explain logs as you code.
• ⏱️ Save hours: No more switching terminals, tailing files, or hunting for errors—get instant feedback and context.
• 🛡️ Safe & isolated: Never pollutes your project, robust CLI and test coverage.
• ⚡ Plug & Play: One command, zero config, works everywhere.

👤 Who is it for?

• Backend & frontend developers
• DevOps & SREs
• Teams using AI-powered editors (Cursor, etc.)
• Anyone who wants faster, smarter log analysis!

📦 Installation

🚀 Automatic (recommended)

npx log-reader-mcp init

• Installs everything, creates .cursor/mcp.json and workflow rules, and sets up your logs folder automatically.

🛠️ Manual

1. Install the package

   npm install --save-dev log-reader-mcp
   

2. Create the config file

   • At the root of your project, create a folder named .cursor (if it doesn't exist).
   • Inside .cursor/, create a file named mcp.json with:

   {
     "mcpServers": {
       "log-reader-mcp": {
         "command": "npx",
         "args": ["-y", "log-reader-mcp"]
       }
     },
     "mcp.enabled": true,
     "mcp.autoStart": true,
     "mcp.showStatusBar": true,
     "mcp.logLevel": "info"
   }
   

   • This tells your editor (Cursor, VSCode, etc.) how to launch and connect to the log reader mcp server for your project.

🖼️ What does it do?

Log Reader Mcp exposes your application's logs to your AI assistant/editor (like Cursor) via the Model Control Protocol (MCP). This means:

• The AI can read, filter, and analyze your logs on demand (not streaming)
• You can ask the AI to fetch logs for a specific period, number of lines, error level, etc.
• Makes onboarding, debugging, and incident response dramatically faster

🔧 Key Features

• Simplified Interface: No logPath parameter needed - always uses logs/logs.log in your working directory
• Automatic Detection: The server automatically finds and reads your log file
• Time-based Filtering: Filter logs by specific time ranges using ISO 8601 format
• Line-based Reading: Read the last N lines with automatic validation
• Structured JSON: Full support for structured logging with metadata

💡 Example Prompts for Cursor

Here are some real-world prompts you can use in Cursor (or any MCP-enabled AI) to interact with your logs:

Note: The tool automatically uses logs/logs.log in your current working directory. The logPath parameter has been removed for maximum simplicity - no need to specify any file path!

Tip: You can combine filters, time ranges, and keywords in your prompts. The AI will use Log Reader Mcp to fetch and analyze the relevant log data for you!

💡 Use Cases

| Use Case | How Log Reader Mcp Helps | Time Saved