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Lumen MCP

by SnipeFactory

๐Ÿง  SnipeFactory: Lumen MCP Engine

Language: English ํ•œ๊ธ€

JVM Flight Recorder (JFR) Forensic Engine for LLM
Hybrid TypeScript/Java MCP Server for Advanced JVM Analysis

Lumen MCP is the analytical brain of the Lumen ecosystem. It leverages a high-performance Java engine to parse JFR files and a TypeScript bridge to provide a seamless Model Context Protocol (MCP) interface for AI agents like Gemini and Claude.


โœจ Key Features

  • Hybrid Intelligence: Combines Java's deep JFR parsing power with Node.js's ecosystem compatibility.

  • Exception Forensics: Trace hidden exceptions (Swallowed Exceptions) with full call chains.

  • SQL & I/O Analytics: Pinpoint slow queries and socket latencies with line-level precision.

  • Smithery Ready: Fully compatible with Smithery CLI for instant distribution.


Related MCP server: Arthas MCP Server

๐Ÿš€ Installation & Setup

1. Build the Project

Lumen MCP requires both Node.js (18+) and Java (11+) to build.

npm install
npm run build

(This command runs tsc for the bridge and ./gradlew installDist for the engine.)

2. Register with Gemini CLI

You can now run Lumen using the Node.js bridge (Recommended):

{
  "mcpServers": {
    "lumen": {
      "command": "node",
      "args": [
        "/path/to/lumen-mcp/dist/server.js"
      ]
    }
  }
}

๐Ÿ” Diagnostic Tools

Tool

Description

analyze_exceptions

Analyzes exception throw points and call chains.

analyze_jdbc_queries

Identifies slow SQL queries and their source lines (Java 11+).

analyze_network_io

Detects socket latency (Essential for Java 8 triage).

analyze_hot_methods

Pinpoints code lines consuming the most CPU cycles.

analyze_memory_usage

Analyzes GC health and object allocation hotspots.

analyze_lock_contention

Identifies thread synchronization bottlenecks.


๐Ÿ“– Usage Example

"Gemini, use lumen to analyze data/incident.jfr. Tell me why the database response is slow."


ยฉ 2026 SnipeFactory. All rights reserved.

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