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PopNx MCPAI를 쓰는 사람을 위한 MCP 서버 · 쉬운 말로 설명해요

Metal GPU Trace

제작자: partprogramming09버전 0.22.0i★ –i내 컴퓨터에서 실행
레지스트리 이름io.github.partprogramming09/metal-gpu-trace

설치

개요

제작자가 쓴 설명(영어 원문)

Measure Wine and macOS programs' GPU use on Apple silicon with Metal System Trace

PopNx MCP의 세 기둥

이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.

할 수 있는 일

이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.

  • 연결 방식: 내 컴퓨터에서 실행
  • 전송 방식: stdio
  • 카테고리: 기타

설치

쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.

설치하기 전에

  • 기본 점검: 1개 중 1개 통과
  • 내 컴퓨터에서 내 사용자 계정의 권한(파일, 네트워크, 앱)으로 실행돼요.
  • 직접 입력할 값: METAL_TRACE_OUT, METAL_TRACE_WINE

필요한 것

  • PyPIPython의 uv 설치(uvx 명령어용)

어떤 앱을 쓰세요?

위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.

Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요

{
  "mcpServers": {
    "metal-gpu-trace": {
      "command": "uvx",
      "args": [
        "metal-gpu-trace"
      ],
      "env": {
        "METAL_TRACE_OUT": "your-value",
        "METAL_TRACE_WINE": "your-value"
      }
    }
  }
}

터미널에서 이 명령어를 실행하세요

claude mcp add metal-gpu-trace --env METAL_TRACE_OUT=your-value --env METAL_TRACE_WINE=your-value -- uvx metal-gpu-trace

실행하기 전에 빈 값을 채워 주세요.

Cursor에서 열기

또는 설정을 직접 복사하기

프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요

{
  "mcpServers": {
    "metal-gpu-trace": {
      "command": "uvx",
      "args": [
        "metal-gpu-trace"
      ],
      "env": {
        "METAL_TRACE_OUT": "your-value",
        "METAL_TRACE_WINE": "your-value"
      }
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

VS Code에서 열기

또는 설정을 직접 복사하기

프로젝트의 .vscode/mcp.json에 붙여 넣으세요

{
  "servers": {
    "metal-gpu-trace": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "metal-gpu-trace"
      ],
      "env": {
        "METAL_TRACE_OUT": "your-value",
        "METAL_TRACE_WINE": "your-value"
      }
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.

선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.

직접 입력할 값

  • METAL_TRACE_OUT env
    Absolute path of the directory where recordings go
  • METAL_TRACE_WINE env
    Wine directory holding bin/wine, used when a recording names none

이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.

할 수 있는 일

내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.

기본 점검i

누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검

  • ✓ 통과

    제작자와 저장소 일치

    레지스트리 이름이 GitHub 계정 partprogramming09 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요

  • … 아직 점검 안 함

    계속 관리되고 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • … 아직 점검 안 함

    라이선스 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • – 해당 없음

    엔드포인트 응답

    내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요

  • – 해당 없음

    OAuth로 로그인

    내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요

  • … 아직 점검 안 함

    도구 설명에 숨겨진 지시 없음

    내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요

기타 카테고리의 다른 서버와 비교i

  • 이 카테고리의 다른 서버 32688개 중 0%보다 스타가 많아요
  • 이 카테고리의 다른 서버 32688개 중 96%보다 최근에 레지스트리에 공개됐어요
  • 기본 점검 결과가 이 카테고리의 다른 서버 32688개 중 100%와 같거나 더 좋아요

레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.

자주 묻는 질문

Metal GPU Trace, 안전한가요?

해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.

어떤 키나 코드가 필요한가요?

레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.

내 컴퓨터에서 실행되나요, 클라우드에서 실행되나요?

내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).

아직 관리되고 있나요?

GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.22.0)은 어제 레지스트리에 올라왔어요.

어떤 앱에서 쓸 수 있나요?

Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.

대신 쓸 수 있는 건 뭐가 있나요?

같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, 御府和田玉 在售作品查询

대안

같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.

카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i

Spec Driven Development

제작자: formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

내 컴퓨터에서 실행★ 440MIT14개월 전 업데이트
설치

Remote Desktop Commander

제작자: desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

클라우드에서 실행★ 211그저께 업데이트
설치

Live in-stock Hetian jade from Yufu, Shanghai: prices, monthly price guide, book a viewing.

클라우드에서 실행오늘 업데이트
설치

제작자의 README

README 열기

제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.

metal-gpu-trace

Measure how a Wine or macOS program uses the GPU on an Apple silicon Mac, from the command line or through an AI coding agent: GPU time per frame, frame pacing, FPS and memory, recorded with Instruments' Metal System Trace; whether a translation layer (DXMT, Mullion, MoltenVK) splits the work into too many short encoders; Metal .gputrace captures read without Xcode; and Apple's published facts on each GPU family to read the numbers against. Python 3.9+ standard library, zsh, and Xcode (for xctrace). MIT license. Español.

FileWhat it does
perf_record.shRecords a program for N seconds with Metal System Trace and writes _ .json (GPU ms per frame, frame intervals, FPS, Metal and resident memory) plus per-frame and memory CSVs. Deletes the .trace afterwards unless KEEP_TRACE=1.
perf_report.pySummarizes an existing .trace the same way.
gputrace_read.pyReads a Metal .gputrace capture without Xcode: command buffers, encoders, draws, debug groups. Call names marked probable are not confirmed.
data/apple-gpu-families.jsonApple7 to Apple10: chips, what each family adds, limits that differ, with Apple's sources.
metal_trace_mcp.pyAn MCP server over all of the above.
test_metal_trace_mcp.pySelf-check without Instruments: python3 -I test_metal_trace_mcp.py prints ok; pytest runs the same tests.

Recording

PERF_OUT=~/perf-runs zsh perf_record.sh game-d3d12 30 /path/to/wine ~/.wine /path/to/game game.exe

PERF_OUT=~/perf-runs zsh perf_record.sh app-metal 30 native - /path/to/app ./app

Arguments: label, seconds, a Wine directory holding bin/wine (or native), the Wine prefix, the working directory, the program and its arguments. Without PERF_OUT, runs go to ./perf-runs. Reading the trace afterwards takes about a minute on an M1 Pro (87 s for a 10 s recording); through the MCP server the whole call times out after 10 s per recorded second plus 120 s, and an overrun recording leaves no files behind. One recording runs at a time; keep other GPU work off the Mac while it records.

Under Wine, give it 30 s: Wine's start-up takes part of the recording. A recording with under 100 frames is too short to compare.

Disk use

Each recording keeps a JSON summary and three CSVs, about 2 MB for 10 s (most of it the Metal memory samples). The .trace (tens to hundreds of MB) is deleted unless KEEP_TRACE=1. KEEP_RUNS=N keeps only the newest N recordings. PERF_MEMORY=0 skips the Metal memory table, the slowest to read: the summary then has no metal_memory_mib and there is no memory CSV (41 % faster to summarize a 626 MB trace). The MCP tools perf_record and perf_baseline_record offer the same as memory=false.

MCP server

Install

The server runs with uvx from PyPI, with nothing to clone (brew install uv installs it). Recording also needs Xcode installed (xcrun xctrace version prints a version).

uvx metal-gpu-trace

This is the command each client below runs. Desktop apps do not see Homebrew's PATH: give them the full path that which uvx prints (/opt/homebrew/bin/uvx on Apple silicon). uvx keeps the version it first downloaded; run the command once with --refresh after uvx to get the latest. uvx metal-gpu-trace@0.4.0 pins a version.

The server reads these environment variables:

VariableWhat it sets
METAL_TRACE_OUTWhere recordings go. Give an absolute path: the default, ./perf-runs, depends on the client's working directory.
METAL_TRACE_WINEThe Wine directory (holding bin/wine) that perf_record uses when the call names none.
WINEPREFIXThe Wine prefix used when the call names none; ~/.wine otherwise.
METAL_TRACE_READMore directories the tools may read, separated by :.
METAL_TRACE_LOGoff silences the one-line stderr log per call.
KEEP_TRACE1 keeps each recording's .trace, for trace_tables, trace_query or Instruments.
KEEP_RUNSKeeps only the newest N recordings.
PERF_ENVNAME=VALUE pairs, separated by spaces, set for the recorded program.
PERF_INSTRUMENTSInstruments added to the Metal System Trace template, separated by ; (xcrun xctrace list instruments names them); their tables need the .trace, so pair it with KEEP_TRACE=1.
Claude Code
claude mcp add --scope user metal-trace -e METAL_TRACE_OUT=$HOME/perf-runs -e METAL_TRACE_WINE=/path/to/wine \

-- uvx metal-gpu-trace claude mcp list

claude mcp list shows metal-trace as connected. --scope user makes it available in every project; leave it out to add it to the current project only.

Windows

On Windows the server records native programs (perf_record_windows.py); no Wine and no Metal. METAL_TRACE_WINE is not needed: perf_record and perf_attach use native. METAL_TRACE_READ is separated by ;.

Frames come from Intel's PresentMon console application (MIT): one row per Present() of the process, with MsBetweenPresents and the GPU time MsGPUTime. Download PresentMon- -x64.exe from its releases, check its SHA-256 against the one GitHub shows, and call the presentmon_install tool, or put it in %LOCALAPPDATA%\metal-gpu-trace or on PATH, or point PRESENTMON_EXE at it. The user must be an administrator or in the "Performance Log Users" group. Without PresentMon the summary falls back to DWM composition intervals (gpu.source is dwm-composition): they cover the whole desktop, miss games in exclusive full screen, and carry no GPU time. With neither a frame log, PresentMon nor DWM samples, a recording fails; it never invents frames.

What cannot be measured is null, not zero: the 1% low needs 100 frames and the 0.1% low 1000; stutter rate and jitter need two frames; thermal_throttling_detected needs GPU times; a drawstress log holds one mean per line, so its summary (gpu.frame_times) has no frame-level percentiles, stutter or jitter. DWM keeps only intervals between consecutive composed frames and drops a jump of several frames. perf_diagnose calls a large working set with uneven frame times MEMORY_PRESSURE_SUSPECTED: a suspicion, since memory bandwidth is not measured.

winget install --id=astral-sh.uv -e

claude mcp add --scope user metal-trace -e METAL_TRACE_OUT=%USERPROFILE%\perf-runs -- uvx metal-gpu-trace claude mcp list

To run from a clone instead of PyPI (needs Python 3.9 or newer):

claude mcp add --scope user metal-trace -e METAL_TRACE_OUT=%USERPROFILE%\perf-runs -- python C:\path\to\metal-gpu-trace\metal_trace_mcp.py

In JSON clients use "command": "uvx" (or the full path where uvx prints) and Windows paths with doubled backslashes. Claude Desktop reads %APPDATA%\Claude\claude_desktop_config.json. Run the Windows tests with python -m pytest test_perf_record_windows.py.

Claude Desktop, Cursor and other JSON clients

These apps do not expand ~ or $HOME: write absolute paths.

{

"mcpServers": { "metal-trace": { "command": "/opt/homebrew/bin/uvx", "args": ["metal-gpu-trace"], "env": { "METAL_TRACE_OUT": "/absolute/path/to/perf-runs", "METAL_TRACE_WINE": "/absolute/path/to/wine" } } } }

ClientFile
Claude Desktop~/Library/Application Support/Claude/claude_desktop_config.json (Settings, Developer, Edit Config); restart the app
Cursor~/.cursor/mcp.json
VS Code.vscode/mcp.json in the project; the top key is servers instead of mcpServers, and the server adds "type": "stdio"
Codex CLI

In ~/.codex/config.toml:

[mcp_servers.metal-trace]

command = "/opt/homebrew/bin/uvx" args = ["metal-gpu-trace"] env = { METAL_TRACE_OUT = "/absolute/path/to/perf-runs", METAL_TRACE_WINE = "/absolute/path/to/wine" }

Tools
ToolReads or records
perf_recordRecords a program and returns its summary; when it ends it stops every program of its Wine prefix, or every process named like a native program. counters=true also records Metal GPU Counters: gpu_counters (the limiters, utilization, occupancy and memory bandwidth of the GPU, with the main limiter) in the summary, at about 40 s of read-back per recorded second; not under Windows
perf_attachRecords a program that is already running, by pid or name, and leaves it running
perf_runsLists recordings, newest first, one page at a time, whether each kept its .trace, and the translation layer it ran on (a fingerprint of its Direct3D DLLs, and its Wine)
perf_compareCompares two recordings: headline numbers, encoders, GPU idle time and each encoder label's GPU ms per frame, largest change first; flags those under 100 frames. markdown=true adds the numbers as Markdown tables for a PR comment; skip_s leaves out the first seconds of each recording (start-up) and recomputes the GPU numbers, hitches and Metal memory without them. perf_gate and perf_panel take skip_s too
perf_baselineSaves several equal recordings as a named reference and returns the range each number spans across them and spread_pct, how much equal runs differ (the noise a change must beat); alone, lists the references. skip_s saves each run without its first seconds and perf_check applies the same cut to the run it judges
perf_baseline_recordRecords the same program count times (default 3) with perf_record's arguments and saves the runs as a reference in one call. skip_s as in perf_baseline
perf_cold_warmRecords the same program twice in a row and says how many more shader-compile hitches the first run has than the second (first_seen_hitches), with each run's hitches, hitches per minute and graphics compiler time; the Metal shader cache is not cleared between them
perf_abRecords the same program with two environments (env_a, env_b: NAME=VALUE pairs) in the order A B B A and says per metric (FPS, 1 % low, GPU ms, stutter) whether B is better, worse or the same: better or worse only when every B value is outside A's range
perf_sweepRecords the same program once per value of one variable (dim, size, example, api or env:NAME), 2 to 8 values, rounds times (every other round in reverse order), and returns per value the median FPS, 1 % low, GPU ms per frame and stutter; with 3 or more numeric values it fits GPU ms per frame on the value (fixed ms and ms per draw for dim) with its r2
perf_checkJudges a recording against a reference: regressed when FPS falls under the range by more than margin_pct (default 3), GPU ms per frame rises over it, or encoders or command buffers per frame exceed it; improved or same otherwise, with the reasons and the full comparison
perf_gateChecks a recording against budgets you set (FPS and 1% low floors; stutter, p95 GPU ms, hitch and Metal MiB ceilings) and returns pass or fail with each limit and value; a missing number fails
perf_historyFollows FPS, 1% low, GPU ms, stutter, hitches and Metal MiB across the runs whose name starts with a prefix, oldest first, with the change from first to last

| perf_panel | Writes .panel.html: a page with GPU time per frame and its hitches, the numbers, Metal memory and, for two runs, A against B. It has no server and loads nothing from the network; the viewer hides or reorders widgets and exports the layout as JSON. With --http, `/panel#token=...&runs=a,b

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