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., "@Lumen MCP Analyze the JFR file incident.jfr for database latency issues."
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.
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.
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
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.)
You can now run Lumen using the Node.js bridge (Recommended):
{
"mcpServers": {
"lumen": {
"command": "node",
"args": [
"/path/to/lumen-mcp/dist/server.js"
]
}
}
}Tool | Description |
| Analyzes exception throw points and call chains. |
| Identifies slow SQL queries and their source lines (Java 11+). |
| Detects socket latency (Essential for Java 8 triage). |
| Pinpoints code lines consuming the most CPU cycles. |
| Analyzes GC health and object allocation hotspots. |
| Identifies thread synchronization bottlenecks. |
"Gemini, use lumen to analyze
data/incident.jfr. Tell me why the database response is slow."
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