Pprof Analyzer MCP

🚀 PProf Usage Guide (Simplified Chinese Version - English Adapted)

This guide provides a comprehensive overview of using PProf, including server - side configuration, client - side usage, prof file analysis, and more.

🚀 Quick Start

Server - side Configuration (Taking Docker as an Example)

# The following is a typical Docker runtime configuration example:
docker run -d --name my-golang-service \
  -p 8080:8080 \
  -v /my/app/path:/app \
  --entrypoint "/app/pprof_server.sh" \
  golang:latest

Client - side Usage Instructions

Configuring MCP Protocol Support (Taking Go Language as an Example)

import (
    "context"
    "fmt"
    "log"
    "net/http"

    "github.com/google/pprof/pkg/collector/collectormiddleware"
    "github.com/google/pprof/pkg/collector/goroutine"
    "github.com/google/pprof/pkg/collector/memory"
    "github.com/google/pprof/pkg/collector/profile"
    "github.com/google/pprof/pkg/collector/sched"
    "github.com/google/pprof/pkg/collector/threadstats"
    "github.com/google/pprof/pkg/frontender"
)

func main() {
    ctx := context.Background()
    
    // Configure performance collection middleware
    middleware := collectormiddleware.New(
        goroutine.NewCollector(),
        memory.NewCollector(),
        profile.NewCollector(),
        sched.NewCollector(),
        threadstats.NewCollector(),
    )

    // Initialize the MCP front - end service
    frontend, err := frontender.New(frontend.Config{
        Middlewares: []frontender.Middleware{middleware},
        Log:         log.New(os.Stdout, "", log.LstdFlags),
    })
    if err != nil {
        log.Fatal(err)
    }

    // Define the handler function
    handler := http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
        // Generate performance data files
        pprof.CreateProfile(ctx, w, r, frontend)
    })

    // Start the HTTP server
    server := &http.Server{
        Addr:    ":8082",
        Handler: handler,
    }

    fmt.Printf("Starting PProf server on :8082\n")
    if err := server.ListenAndServe(); err != nil {
        log.Fatal(err)
    }
}

💻 Usage Examples

Analyzing prof Files

Analyzing Local prof Files

# Download and install the PProf tool
go install github.com/google/pprof/cmd/llhttp@latest
go install github.com/google/pprof/pprof/...

Command - line Analysis Example

# View the goroutine profile
pprof -text ./myapp goroutine

# Generate a flame graph
pprof -svg ./myapp cpu > my_flame_graph.svg

# Analyze memory allocation
pprof -http ./myapp heap

Analyzing Using the MCP Protocol (HTTP Method)

{
    "tool_name": "analyze_pprof",
    "arguments": {
        "profile_uri": "http://localhost:8082/debug/pprof/profile?uid=123456&type=cpu",
        "profile_type": "cpu",
        "top_n": 5,
        "output_format": "text"
    }
}

Example of Analyzing Remote prof Files

# Download an online prof file
curl -o my_profile.cpu https://example.com/pprof/cpu

# Analyze the downloaded prof file
pprof -http ./myapp my_profile.cpu

Flame Graph Generation and Viewing

Local Flame Graph Generation

# Generate an SVG - format flame graph directly using the PProf tool
pprof -svg ./myapp cpu > my_flame_graph.svg

# Or use the following command:
go tool pprof -svg ./myapp cpu > my_flame_graph.svg

Online Flame Graph Viewing

# Start the PProf HTTP service
go tool pprof ./myapp

# Access address: http://localhost:8082/debug/pprof

Using the MCP Protocol for Performance Analysis (Go Language Client)

import (
    "context"
    "log"
    "net/http"

    "github.com/google/pprof/pkg/frontender"
)

func main() {
    ctx := context.Background()

    // Initialize the MCP front - end service
    frontend, err := frontender.New(frontend.Config{
        Middlewares: []frontender.Middleware{
            // Add the required performance collection middleware
            goroutine.NewCollector(),
            memory.NewCollector(),
        },
        Log: log.New(os.Stdout, "", log.LstdFlags),
    })
    if err != nil {
        log.Fatal(err)
    }

    // Create an HTTP client
    client := &http.Client{}

    // Send a performance data collection request
    resp, err := client.Get("http://localhost:8082/debug/pprof/profile")
    if err != nil {
        log.Fatal(err)
    }
    defer resp.Body.Close()

    // Process the response content (custom processing logic can be defined)
    // For example: parse performance data and perform analysis
}

📚 Documentation

Configuration Reference

HTTP Service Configuration Example

# Example script content for pprof_server.sh:
#!/bin/bash
set -eo pipefail

APP_PATH="/app/myapp"
CPU_PROFILE=/my/app/path/profiles/cpu.pprof
MEM_PROFILE=/my/app/path/profiles/mem.pprof

cd ${APP_PATH}

exec "$@" 

Environment Variable Configuration Example

# Set environment variables related to performance analysis
export GODEBUG="gcflags='-http2 profiling'"
export PPprof Addr=0.0.0.0:8082

Toolchain Integration

CI/CD Pipeline Integration (Jenkins Example)

pipeline {
    agent any
    stages {
        stage('Build') {
            steps {
                sh 'go build -o myapp .' # Compile the program
            }
        }
        stage('Profile') {
            steps {
                sh 'go install github.com/google/pprof/cmd/llhttp@latest' # Install the PProf tool
                sh 'go test -bench . -run=' # Execute benchmark tests
                sh 'go tool pprof -text ./myapp cpu > profiling_results.txt' # Generate a text - format performance report
            }
        }
    }
}

Troubleshooting Common Issues

Network Connection Issues

• Check the firewall settings to ensure that port 8082 is open.
• Use the netstat -tuln | grep 8082 command to confirm if the service is listening on this port.

Incomplete Performance Data

• Ensure that all necessary performance collection middleware is correctly configured.
• Check the log output to ensure there are no error messages.

Installation Issues

• Ensure that the Go language environment is correctly configured and the version is not lower than 1.20.
• Use the go version command to confirm the current Go version.

Reference Materials

1. Golang Official Documentation
2. PProf Tool Documentation
3. Best Practices for Performance Analysis

Appendix

Common Commands

# View the goroutine status of the currently running process
go tool pprof -text ./myapp goroutine

# Analyze memory allocation
go tool pprof -http ./myapp mem

# Generate a flame graph (CPU profiling)
go tool pprof -svg ./myapp cpu > my_flame_graph.svg

# View help information
pprof --help

Environment Variable Configuration Recommendations

export GOGC=off # Turn off Go's garbage collection mechanism
export GODEBUG="gcflags='-http2 profiling'" # Enable HTTP/2 performance analysis support
export PPprof.Addr=0.0.0.0:8082 # Set the PProf service listening address

Additional Resources

• In - depth Understanding of Golang's Memory Management
• Comparison of Performance Analysis Tools