Perfetto Mcp

Perfetto MCP

> Turn natural language into powerful Perfetto trace analysis

A Model Context Protocol (MCP) server that transforms natural-language prompts into focused Perfetto analyses. Quickly explain jank, diagnose ANRs, spot CPU hot threads, uncover lock contention, and find memory leaks – all without writing SQL.

✨ Features

• Natural Language → SQL: Ask questions in plain English, get precise Perfetto queries
• ANR Detection: Automatically identify and analyze Application Not Responding events
• Performance Analysis: CPU profiling, frame jank detection, memory leak detection
• Thread Contention: Find synchronization bottlenecks and lock contention
• Binder Profiling: Analyze IPC performance and slow system interactions

📋 Prerequisites

• Python 3.13+ (macOS/Homebrew):

``bash brew install python@3.13 ``

• uv (recommended):

``bash brew install uv ``

🚀 Getting Started

Cursor

[](https://cursor.com/install-mcp?name=perfetto-mcp&config=eyJjb21tYW5kIjoidXZ4IHBlcmZldHRvLW1jcCJ9)

Or add to ~/.cursor/mcp.json (global) or .cursor/mcp.json (project):

{
  "mcpServers": {
    "perfetto-mcp": {
      "command": "uvx",
      "args": ["perfetto-mcp"]
    }
  }
}

Claude Code

Run this command. See Claude Code MCP docs for more info.

# Add to user scope
claude mcp add perfetto-mcp --scope user -- uvx perfetto-mcp

Or edit ~/claude.json (macOS) or %APPDATA%\Claude\claude.json (Windows):

{
  "mcpServers": {
    "perfetto-mcp": {
      "command": "uvx",
      "args": ["perfetto-mcp"]
    }
  }
}

VS Code

[](https://insiders.vscode.dev/redirect?url=vscode%3Amcp%2Finstall%3F%7B%22name%22%3A%22perfetto-mcp%22%2C%22type%22%3A%22stdio%22%2C%22command%22%3A%22uvx%22%2C%22args%22%3A%5B%22perfetto-mcp%22%5D%7D)

or add to .vscode/mcp.json (project) or run "MCP: Add Server" command:

{
  "mcpServers": {
    "perfetto-mcp": {
      "command": "uvx",
      "args": ["perfetto-mcp"]
    }
  }
}

Enable in GitHub Copilot Chat's Agent mode.

Codex

Edit ~/.codex/config.toml:

[mcp_servers.perfetto-mcp]
command = "uvx"
args = ["perfetto-mcp"]

Optional: Use a Local trace_processor_shell Binary

If your network environment blocks downloads, set PERFETTO_MCP_TRACE_PROCESSOR_BIN_PATH to an absolute path of a local trace_processor_shell binary.

When this env var is set, perfetto-mcp uses that binary directly. When it is not set, default perfetto Python behavior is unchanged.

Example (mcp.json):

{
  "mcpServers": {
    "perfetto-mcp": {
      "command": "uvx",
      "args": ["perfetto-mcp"],
      "env": {
        "PERFETTO_MCP_TRACE_PROCESSOR_BIN_PATH": "D:/tools/perfetto/trace_processor_shell.exe"
      }
    }
  }
}

Example (~/.codex/config.toml):

[mcp_servers.perfetto-mcp]
command = "uvx"
args = ["perfetto-mcp"]
[mcp_servers.perfetto-mcp.env]
PERFETTO_MCP_TRACE_PROCESSOR_BIN_PATH = "D:/tools/perfetto/trace_processor_shell.exe"

Local Install (development server)

cd perfetto-mcp-server
uv sync
uv run mcp dev src/perfetto_mcp/dev.py

Local MCP

{
  "mcpServers": {
    "perfetto-mcp-local": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/git/repo/perfetto-mcp",
        "run",
        "-m",
        "perfetto_mcp"
      ],
      "env": { "PYTHONPATH": "src" }
    }
  }
}

Using pip

pip3 install perfetto-mcp
python3 -m perfetto_mcp

📖 How to Use

Example starting prompt: > In the perfetto trace, I see that the FragmentManager is taking 438ms to execute. Can you figure out why it's taking so long?

Required Parameters

Every tool needs these two inputs:

| Parameter | Description | Example | |-----------|-------------|---------| | tracepath | Absolute path to your Perfetto trace | /path/to/trace.perfetto-trace | | processname | Target process/app name | com.example.app |

In Your Prompts

Be explicit about the trace and process, prefix your prompt with:

"Use perfetto trace /absolute/path/to/trace.perfetto-trace for process com.example.app"

Optional Filters

Many tools support additional filtering (but let your LLM handle that):

• time_range: {start_ms: 10000, end_ms: 25000}
• Tool-specific thresholds: min_block_ms, jank_threshold_ms, limit

🛠️ Available Tools

🔎 Exploration & Discovery

| Tool | Purpose | Example Prompt | |------|---------|----------------| | find_slices | Survey slice names and locate hot paths | "Find slice names containing 'Choreographer' and show top examples" | | execute_sql_query | Run custom PerfettoSQL for advanced analysis | "Run custom SQL to correlate threads and frames in the first 30s" |

🚨 ANR Analysis

Note: Helpful if the recorded trace contains ANR

| Tool | Purpose | Example Prompt | |------|---------|----------------| | detect_anrs | Find ANR events with severity classification | "Detect ANRs in the first 10s and summarize severity" | | anr_root_cause_analyzer | Deep-dive ANR causes with ranked likelihood | "Analyze ANR root cause around 20,000 ms and rank likely causes" |

🎯 Performance Profiling

| Tool | Purpose | Example Prompt | |------|---------|----------------| | cpu_utilization_profiler | Thread-level CPU usage and scheduling | "Profile CPU usage by thread and flag the hottest threads" | | main_thread_hotspot_slices | Find longest-running main thread operations | "List main-thread hotspots >50 ms during 10s–25s" |

📱 UI Performance

| Tool | Purpose | Example Prompt | |------|---------|----------------| | detect_jank_frames | Identify frames missing deadlines | "Find janky frames above 16.67 ms and list the worst 20" | | frame_performance_summary | Overall frame health metrics | "Summarize frame performance and report jank rate and P99 CPU time" |

🔒 Concurrency & IPC

| Tool | Purpose | Example Prompt | |------|---------|----------------| | thread_contention_analyzer | Find synchronization bottlenecks | "Find lock contention between 15s–30s and show worst waits" | | binder_transaction_profiler | Analyze Binder IPC performance | "Profile slow Binder transactions and group by server process" |

💾 Memory Analysis

| Tool | Purpose | Example Prompt | |------|---------|----------------| | memory_leak_detector | Find sustained memory growth patterns | "Detect memory-leak signals over the last 60s" | | heap_dominator_tree_analyzer | Identify memory-hogging classes | "Analyze heap dominator classes and list top offenders" |

Output Format

All tools return structured JSON with:

• Summary: High-level findings
• Details: Tool-specific results
• Metadata: Execution context and any fallbacks used

📚 Resources

• Trace Processor Python API - Perfetto's Python interface
• Perfetto SQL Syntax - SQL reference for custom queries

📄 License

Apache 2.0 License. See LICENSE for details.

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GitHub • Issues • Documentation

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: antarikshc
• Source: antarikshc/perfetto-mcp
• License: Apache-2.0

Install and usage instructions live in the source repository linked above.