Claude Code Telemetry 📊

See exactly how you/your team uses Claude Code
Track costs, usage patterns, and session data in real-time

https://github.com/user-attachments/assets/2634cec3-94af-4a2d-90da-44cd641f1746

🎯 What This Actually Does

Claude Code Telemetry is a lightweight bridge that captures telemetry data from Claude Code and forwards it to Langfuse for visualization. You get:

• 💰 Cost Tracking - See costs per session, user, and model
• 📊 Usage Metrics - Token counts, cache hits, and tool usage
• ⏱️ Session Grouping - Automatically groups work into 1-hour sessions
• 🔍 Full Transparency - Every API call logged with complete details
• 🔐 Safe local data - The packaged self-hosted Langfuse keeps your data local

The original motivation from the author was that when using Claude Code Pro/Max, it didn't have good options for telemetry out of the box compared to API-based requests that can be integrated with various solutions and wanted to provide a secure turnkey local setup for people using Claude Code to benefit from.

🏗️ Built on Standards

Uses OpenTelemetry for data collection, Langfuse for visualization, and Claude's native observability APIs. No proprietary formats, no vendor lock-in.

🚀 Quick Start (30 seconds)

Prerequisites

🐳 Docker Desktop - Install here if you don't see the whale icon in your menu bar

Setup

# Clone and enter directory
git clone https://github.com/lainra/claude-code-telemetry && cd claude-code-telemetry

# Run automated setup
./quickstart.sh

# Enable telemetry
source claude-telemetry.env

# Test it works
claude "What is 2+2?"

That's it! View your dashboard at http://localhost:3000

Need Help?

Let Claude guide you through the setup:

claude "Set up the telemetry dashboard"

📸 What You'll See in Langfuse

Session View

Every conversation becomes a trackable session:

Session: 4:32 PM - 5:15 PM (43 minutes)
├── Total Cost: $18.43
├── API Calls: 6 (2 Haiku, 4 Opus)
├── Total Tokens: 45,231 (31,450 cached)
├── Tools Used:
│   ├── Read: 23 calls
│   ├── Edit: 8 calls
│   ├── Bash: 4 calls
│   └── Grep: 2 calls
└── Cache Savings: $12.30 (40% cost reduction)

Individual API Calls

Full details for every Claude interaction:

4:45 PM - claude-3-opus-20240229
├── Input: 12,453 tokens (8,234 from cache)
├── Output: 3,221 tokens
├── Cost: $4.87
├── Duration: 3.2s
└── Context: Feature implementation

Cost Breakdown

Track spending by model and user:

Today's Usage:
├── Total: $67.43
├── By Model:
│   ├── Opus: $61.20 (91%)
│   └── Haiku: $6.23 (9%)
└── By User:
    ├── alex@team.com: $28.90
    ├── sarah@team.com: $22.15
    └── mike@team.com: $16.38

🔧 How It Works

Claude Code → OpenTelemetry → Telemetry Bridge → Langfuse
     ↓              ↓               ↓                ↓
  User asks     Sends OTLP    Parses & forwards   Shows in
  questions    telemetry data   to Langfuse       dashboard

The bridge:

1. Listens for OpenTelemetry data from Claude Code
2. Enriches it with session context
3. Forwards to Langfuse for visualization
4. Groups related work into analyzable sessions

🌟 What This Tool Is (and Isn't)

✅ What It Does:

• Tracks costs - Know exactly what you're spending
• Shows usage patterns - See when and how Claude is used
• Groups work sessions - Understand complete tasks, not just individual calls
• Provides full transparency - Every token and dollar accounted for
• Runs locally - Your data stays on your infrastructure

❌ What It Doesn't Do:

• Measure productivity - Can't tell if you're working faster
• Analyze code quality - Doesn't evaluate AI-generated code
• Provide strategic insights - Just shows raw data, not recommendations
• Enable team collaboration - No sharing or pattern discovery features
• Calculate ROI - You'll need to determine value yourself

🛠️ Installation Options

Option 1: Full Stack (Recommended)

Includes Langfuse dashboard + telemetry bridge:

./quickstart.sh

Option 2: Bridge Only (Manual w/NPM)

Already have Langfuse? Just run the bridge:

# Configure your existing Langfuse credentials
export LANGFUSE_PUBLIC_KEY=your-public-key
export LANGFUSE_SECRET_KEY=your-secret-key
export LANGFUSE_HOST=your-langfuse-url

# Install and start the bridge
npm install
npm start

Option 3: Bridge Only (Docker)

Already have Langfuse? Run the bridge in Docker:

# Create .env file with your Langfuse credentials
cp .env.example .env
# Edit .env with your LANGFUSE_PUBLIC_KEY, LANGFUSE_SECRET_KEY, and LANGFUSE_HOST

# Run just the telemetry bridge container
docker compose up telemetry-bridge

📋 Requirements

• Docker Desktop (install) - For quickstart
• Claude Code CLI (claude)
• Node.js 18+ (optional) - For bridge-only mode

🎛️ Configuration

See .env.example for all options.

🔒 Privacy & Security

• 100% Local - No external services unless you configure them
• No Code Storage - Only metadata about interactions
• You Control the Data - Runs on your infrastructure
• Optional Prompt Logging - Choose whether to log prompts

📚 Documentation

• Environment Variables - Complete configuration guide
• Telemetry Guide - Understanding the data format

🤔 Should You Use This?

Use this if you want to:

• Track Claude Code costs across your team
• Understand usage patterns and peak times
• Have transparency into AI tool spending
• Keep telemetry data on your own infrastructure

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

📄 License

MIT License - see LICENSE for details.

Simple, honest telemetry for Claude Code
100% AI-assisted repository, made with ❤️ by Claude and @lainra

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