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uProf MCP Server

A Model Context Protocol (MCP) server for profiling x86 CPU applications using AMD uProf. This package enables LLMs to analyze CPU performance hotspots through the AMD uProf profiler.

Features

CPU Hotspot Profiling (uprof-profiler-mcp)

Tool for profiling x86 CPU executables to identify performance hotspots using AMD uProf.

Capabilities:

  • Profile CPU applications for hotspot analysis
  • Identify top functions consuming CPU time
  • Generate detailed profiling reports
  • Support for custom executable arguments

Installation

You can install the package directly using uv or pip.

# Using uv (recommended)
uv pip install .

# Using pip
pip install .

Configuration

To use this server with an MCP client, add the following to your configuration file:

{
  "mcpServers": {
    "uprof-profiler-mcp": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/uprof_mcp", "uprof-profiler-mcp"]
    }
  }
}

Note: Adjust /path/to/uprof_mcp to the actual path where you have cloned or installed the package.

Usage

Python API (Non-Agentic Mode)

You can use the profiler directly without MCP:

import tempfile
from uprof_mcp.uprof_profiler import UProfProfiler

profiler = UProfProfiler()

with tempfile.TemporaryDirectory() as tmpdir:
    result = profiler.find_hotspots(
        output_dir=tmpdir,
        executable="./my_app",
        executable_args=["arg1", "arg2"],
    )

    with result.report_path.open() as report:
        print(report.read())

Example with LangChain

See examples/uprof_profiler.py for a complete example using LangChain agents:

# Agentic mode (with LLM)
python examples/uprof_profiler.py --executable ./my_app --args arg1 arg2

# Non-agentic mode (direct profiling)
python examples/uprof_profiler.py --executable ./my_app --args arg1 arg2 --classic

Requirements

  • Python >= 3.10
  • AMD uProf installed
  • x86 CPU architecture

Development

This project uses uv for dependency management.

  1. Sync dependencies:

    uv sync --dev

  2. Run the server locally (for testing):

    uv run uprof-profiler-mcp

  3. Run tests:

    pytest

API Reference

UProfProfiler Class

from uprof_mcp.uprof_profiler import UProfProfiler

profiler = UProfProfiler(logger=None)

Methods:

  • find_hotspots(output_dir, executable, executable_args) → UProfProfilerResult
    • Profiles the executable and returns hotspot analysis
    • Parameters:
      • output_dir (str | Path): Directory to store results
      • executable (str | Path): Path to executable
      • executable_args (list[str] | None): Arguments for the executable
    • Returns: UProfProfilerResult with report_path attribute