Arthas Skills

Arthas MCP Server

This skill connects to a fixed Arthas MCP endpoint:

• http://localhost:8563/mcp

Use it when the user wants Arthas-based JVM diagnostics, including:

• Java process and runtime inspection
• Thread blocking, CPU spikes, and deadlock triage
• Method tracing and call-path analysis
• Class, bytecode, and classloader inspection
• Exception-path observation
• Online troubleshooting with Arthas commands exposed as MCP tools

What To Load

• Start here for the workflow and command discipline.
• Read references/arthas-workflows.md when the task is about:
  • high CPU, blocking, deadlock, request latency, or hotspots
  • method entry/exit observation with watch
  • call stack or call path investigation with stack or trace
  • class decompilation / code inspection with jad
  • ongoing metrics with monitor

Operating Rules

• Treat the endpoint as fixed. Do not ask the user to provide a host or port unless they explicitly ask to change the skill itself.
• Prefer low-risk diagnostics first. Start from broad observation before attaching high-cardinality tracing.
• If the user has not identified the application/process yet, use the Arthas MCP tools to discover the available JVM targets before deeper diagnostics.
• Explain performance risk before using commands that can add noticeable overhead, especially wide trace, frequent watch, or long-running monitor.
• Keep probes narrow:
  • target one class or method at a time
  • add conditions where possible
  • limit sample counts and duration when the tool supports it
• When the task is ambiguous, use this sequence:
  1. inspect available processes / sessions
  2. inspect runtime overview
  3. inspect threads or hotspots
  4. narrow to classes and methods
  5. trace or watch the smallest useful scope

Tool Discovery

List the available Arthas MCP tools:

cd $SKILL_DIR
python executor.py --list

Inspect one tool's schema:

cd $SKILL_DIR
python executor.py --describe TOOL_NAME

Call a tool:

cd $SKILL_DIR
python executor.py --call '{"tool":"TOOL_NAME","arguments":{"key":"value"}}'

Recommended Diagnostic Flow

1. Confirm target scope

• Find the available JVM / target-selection tools first.
• If multiple applications are present, select the target before deeper analysis.

2. Start broad

Prefer tools that map to Arthas commands such as:

• dashboard
• thread
• sysprop
• sysenv
• jvm

Use these to determine whether the problem looks like CPU saturation, blocked threads, GC pressure, classloader issues, or slow business methods.

3. Narrow to code paths

For code-level diagnosis, look for tools that map to:

• jad
• sc
• sm
• trace
• stack
• watch
• monitor

Recommended progression:

• Use jad / sc / sm to identify the exact class and method.
• Use stack when you need who-called-this visibility.
• Use trace when you need per-invocation timing along a call path.
• Use watch when you need parameters, return values, or thrown exceptions.
• Use monitor when you need a lightweight rolling view over time.

4. Summarize carefully

• Separate facts from inference.
• Include the exact class, method, condition, and sampling scope used.
• Mention if the MCP endpoint itself failed, timed out, or did not expose the expected tool.

Failure Handling

If a call fails, first distinguish which layer failed:

• Skill/runtime issue: python or mcp package problem
• MCP transport issue: http://localhost:8563/mcp unreachable or returns protocol errors
• Arthas-side issue: target JVM not attached, command unsupported, or selection incomplete
• Input issue: wrong tool name or missing arguments

The current environment may expose the Arthas Console web UI on http://localhost:8563/ even if /mcp is not enabled. If --list or --describe fails with session or protocol errors, report that the fixed endpoint exists in skill config but the MCP route may not be active yet.

Response Style

• Keep operational summaries concise and evidence-based.
• For production-like troubleshooting, call out risky probes before using them.
• When possible, propose the next safest narrowing step instead of jumping straight to a broad trace.