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mag123c/toktrack

Ultra-fast token & cost tracker for LLM Token Usage (e.g. Claude Code)

Rust ◇ ai-billing MIT
★193STARS
⑂21FORKS
!1ISSUES
🏆#12,033GLOBAL RANK
🔥13DAYS TRENDING
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Momentum

+10

STARS · LAST 30 DAYS

1

PER DAY

#1,149

MOST-STARRED Rust

Window7 days30 days90 days
Stars gained+0+10+90
Per day111
Forks gained+0+3+10

toktrack gained 10 stars in the last 30 days, about 1 a day, and now has 193. It is about 1 year old and has averaged roughly 193 stars a year. It ranks #1,149 among Rust repositories and #12,033 across all languages on GitHubRepo.

Trending Record

toktrack has maintained a continuous presence across global trending indexes, peaking at #7335. Below is the 30-day activity profile:

💡 Overview

toktrack is an open-source project written in Rust: Ultra-fast token & cost tracker for LLM Token Usage (e.g. Claude Code).

Engineered for speed, consistency, and developer ease, it solves common hurdles in ai-billing, ai-coding, ai-cost. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

⚡ Key Features

1

Optimized execution pipeline written in Rust for predictable speed.

2

Zero-friction configuration with comprehensive sensible defaults out of the box.

3

Cross-platform runtime support across Linux, macOS, and Windows environments.

4

Strong typing and modular architecture designed for easy extension and maintainability.

5

Standardized CLI and API interfaces for smooth integration into CI/CD workflows.

6

Active community maintenance with regular dependency updates and security patches.

📥 Installation

terminal
$ cargo install toktrack

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Rust toolchain (rustc / cargo >= 1.70)

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

toktrack coordinates its core functionality through a modular Rust pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

🎯 Production Use Cases

Autonomous AI Agents

Orchestrate intelligent workflows and tool-calling routines with toktrack.

Model Inference & Prompting

Integrate fast, local or cloud-hosted generative AI models directly into production code.

Context Memory & RAG

Augment language models with dynamic vector retrieval and structured project memory.

Developer Productivity

Automate repetitive engineering tasks, code generation, and test creation using AI agents.

🚀 Getting Started

1

Install toktrack using your package manager: `cargo install toktrack`

2

Initialize your project workspace or configuration file for toktrack.

3

Import toktrack into your codebase or invoke it directly from your terminal.

4

Execute your test suite or run `toktrack --help` to verify successful setup.

👍 Strengths

Active community backing with 193 GitHub stars and verified adoption.
Permissive open-source distribution under the MIT license.
Built in Rust for high execution speed and developer familiarity.
Cross-platform compatibility across modern Linux, macOS, and Windows environments.
Clean modular design allowing flexible configuration and pipeline integration.

⚠️ Considerations

Requires familiarity with Rust and modern CLI workflows.
Ecosystem extensions may require manual configuration depending on environment constraints.
Active development roadmap means breaking API changes may occur across major versions.

⇄ Alternatives & Direct Competitors

💡
Open Source Alternative to OpenAI API & ChatGPT Replaces proprietary subscriptions (Pay-per-token pricing with zero private data guarantees) with self-hosted freedom.
Explore all OpenAI API & ChatGPT alternatives →
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👥 Who Should Use This

Developers and engineering teams building with Rust, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

mag123c/toktrack is currently ranked #12,033 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
#12,010 transferia/transferia Go ★ 194 Compare ↗
#12,010 StudentWeis/ropy Rust ★ 194 Compare ↗
#12,010 screentinker/screentinker JavaScript ★ 194 Compare ↗
#12,010 orbi-build/orbi Python ★ 194 Compare ↗
#12,010 Own716/OwnBoxForAndroid Kotlin ★ 194 Compare ↗
#12,033 mag123c/toktrack This Project Rust ★ 193
#12,033 ghewgill/emulino C ★ 193 Compare ↗
#12,033 basecamp/trashed Ruby ★ 193 Compare ↗
#12,033 rails/dynamic_form Ruby ★ 193 Compare ↗
#12,033 sibartlett/Geo C# ★ 193 Compare ↗
#12,033 mattbrictson/bundleup Ruby ★ 193 Compare ↗
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Frequently Asked Questions

What does toktrack do? +

Ultra-fast token & cost tracker for LLM Token Usage (e.g. Claude Code)

What language is toktrack written in? +

The primary language is Rust. Topics include: ai-billing, ai-coding, ai-cost, ai-tools, anthropic.

Is toktrack actively maintained? +

Yes, the last recorded push was on Oct 1, 2026 with 1 open issues being tracked.

How many stars does toktrack have? +

toktrack has 193 stars and 21 forks on GitHub.

How does toktrack rank among GitHub repositories? +

With 193 stars, mag123c/toktrack is ranked #12,033 globally across all repositories tracked on GitHubRepo and #1,149 among Rust projects.

What license is toktrack distributed under? +

The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.

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