Monitor and Optimize Claude Code Usage: Best Open-Source Tools for Developers

Efficiently managing AI-assisted coding tools like Anthropic’s Claude Code is now essential for API developers, backend engineers, and technical leads. While Claude Code accelerates software development—auto-generating code, debugging, and more—it can also introduce hidden costs, performance issues, and usage blind spots if left unmonitored.

How can you ensure you’re maximizing value, controlling costs, and proactively optimizing your Claude Code workflow?
The answer lies in powerful open-source monitoring tools designed for developers and teams. In this guide, we’ll compare three top open-source solutions for tracking, analyzing, and managing Claude Code usage—from simple CLI utilities to full-stack observability platforms.

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Why Monitoring Claude Code Usage Matters

AI coding assistants like Claude Code are transforming developer workflows, but without visibility into usage, you risk:

Unexpected cost overruns and wasted budget
Hitting token or session limits at critical moments
Missed opportunities for optimizing model selection and workflow
Lack of data to measure real productivity gains

While Claude Code offers basic usage stats, open-source monitoring tools unlock deeper insights—helping both individual engineers and teams make data-driven decisions, optimize spend, and avoid workflow disruptions.

The 3 Best Open-Source Tools for Monitoring Claude Code Usage

We’ll dive into the architecture, features, and ideal use cases for:

ccusage: A fast CLI for ad-hoc usage and cost analysis
Claude-Code-Usage-Monitor: A live, interactive dashboard for real-time session management
claude-code-otel: An enterprise-grade, self-hosted observability stack for teams

ccusage: Lightweight CLI for Instant Claude Code Usage Reports

Who it’s for:
Individual developers who need quick, clear answers about their Claude Code usage and costs—right from the terminal, with no setup overhead.

Key Features

Multiple Report Types: View daily, monthly, session-based, and “block” (5-hour billing window) usage.
Live Monitoring: Track your current session in real-time, including token “burn rate” and projected costs (blocks --live).
Cost & Model Breakdown: See token usage and costs by model (Opus, Sonnet, Haiku).
Flexible Output: Human-readable tables adapt to terminal width; export data to JSON for scripting.
Zero-Install Option: Run instantly via npx—no installation required.

How ccusage Works

Parses .jsonl log files in your local Claude Code config (~/.config/claude/logs/)
Aggregates prompt and response token counts
Applies current model pricing
Outputs clean, tabular reports (offline, after initial price cache)

Example Usage

Quick daily report:
```
npx ccusage@latest
```
Monthly summary:
```
npx ccusage@latest monthly
```
Live session monitoring:
```
npx ccusage@latest blocks --live
```
JSON export for automation:
Add --json to any command.

Best For

Developers wanting to answer: “How much did I spend yesterday?”
Quick checks after coding sessions
Integrating usage data into custom scripts

Claude-Code-Usage-Monitor: Real-Time Terminal Dashboard

Who it’s for:
Developers who need to actively manage their session limits and avoid being cut off—especially on free or Pro plans.

Key Features

Live Updating Dashboard: Refreshes token usage every 3 seconds.
Predictive Burn Rate: Estimates when your session will hit its token cap.
Visual Progress Bars: Color-coded indicators for token and time remaining.
Plan & Timezone Awareness: Supports multiple plans; adjust for your timezone and session resets.
Proactive Alerts: Warns as you approach session or token limits.

How It Works

Monitors local Claude Code .jsonl logs
Tracks your 5-hour rolling session in real-time
Written in Python; uses the rich library for a polished TUI

Setup & Usage

Install uv (Python installer):

curl -LsSf https://astral.sh/uv/install.sh | sh

Install the monitor:
```
uv tool install claude-monitor
```
Run the dashboard:
```
claude-monitor
```

Customize plan/timezone:

claude-monitor --plan max20 --timezone America/New_York

Best For

Developers on strict token/session limits
Long coding sessions where unexpected lockouts are costly
Visual learners who prefer dashboards over static reports

claude-code-otel: Team-Wide Observability with OpenTelemetry

Who it’s for:
Engineering teams and organizations needing centralized monitoring, cost control, and security for Claude Code usage.

Key Features

Complete Observability Stack: Integrates OpenTelemetry, Prometheus, Loki, and Grafana.
Comprehensive Dashboards: Analyze cost, user activity, productivity, API latency, errors, and more.
Team-Wide Monitoring: Aggregate and visualize usage across many users/projects.
Data Sovereignty: Self-hosted—keep usage and prompt data secure and private.
Vendor-Neutral Standards: Built on OpenTelemetry for extensibility.

How It Works

Claude Code CLI emits telemetry via OpenTelemetry when enabled
claude-code-otel (via Docker Compose) collects, stores, and visualizes metrics/logs:
- Prometheus: For real-time metrics (tokens, cost, latency)
- Loki: For event logs (prompts, errors)
- Grafana: For rich, interactive dashboards

Setup Steps

Clone the repo:

git clone https://github.com/ColeMurray/claude-code-otel.git
cd claude-code-otel

Start the stack:
```
make up
```

Configure Claude Code CLI:

export CLAUDE_CODE_ENABLE_TELEMETRY=1
export OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
# ...additional env vars as documented

Access dashboards:
Open http://localhost:3000 in your browser.

Best For

Teams managing shared Claude Code budgets
Platform engineers tracking reliability and performance
Organizations needing secure, centralized AI usage analytics

Choosing the Right Monitoring Tool

For solo devs: Start with ccusage for fast, simple usage and cost insights.
For session management: Use Claude-Code-Usage-Monitor for live, proactive token tracking.
For teams/orgs: Deploy claude-code-otel for comprehensive, secure observability and management.

By adopting the right tool, you’ll gain control over Claude Code usage, prevent surprises, and optimize your AI-assisted development workflow.

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