tokentelemetry
Health Warn
- License — License: MIT
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Low visibility — Only 8 GitHub stars
Code Fail
- child_process — Shell command execution capability in bin/cli.js
- spawnSync — Synchronous process spawning in bin/cli.js
- process.env — Environment variable access in bin/cli.js
- fs module — File system access in bin/cli.js
- network request — Outbound network request in frontend/src/app/analytics/page.tsx
- network request — Outbound network request in frontend/src/app/locallab/page.tsx
Permissions Pass
- Permissions — No dangerous permissions requested
This tool provides a local, unified dashboard for monitoring token usage, API costs, session traces, and tool calls across multiple AI coding agents like Claude Code, Gemini CLI, and Cursor.
Security Assessment
Overall Risk: Medium. The CLI component heavily relies on shell command execution (`child_process`, `spawnSync`), which is expected for a tool that parses local system logs, but it does expand the potential attack surface if compromised. It also accesses environment variables and the local file system to read agent histories. The project claims to be 100% local, but the frontend code contains outbound network requests in its analytics and local lab pages. Developers should verify what data these requests send, as it may conflict with the "no telemetry" promise. No hardcoded secrets or explicitly dangerous permissions were found.
Quality Assessment
The project is very new and currently has low community visibility with only 8 GitHub stars. However, it is actively maintained (last push was today), clearly documented, and uses a standard MIT license. Because it is early in its lifecycle, it should be considered in active development rather than battle-tested.
Verdict
Use with caution — the concept is highly useful and safe in theory, but you should inspect the code yourself to verify the frontend network requests and ensure no sensitive data leaves your machine.
Token telemetry dashboard for AI coding agents — tracks tokens, sessions, tool calls & reasoning across Claude Code, Gemini CLI, Codex & more. 100% local. tokentelemetry.com
TokenTelemetry
Local token + cost monitoring dashboard for AI coding agents — Claude Code, Gemini CLI, Codex, Cursor, GitHub Copilot, OpenCode, and more.
TokenTelemetry is a free, open-source, 100% local observability dashboard that tracks token usage, LLM costs, tool calls, session traces, and reasoning steps across all your AI coding agents — in one unified place. No signup. No cloud. No telemetry.
🌐 Website & Docs: https://tokentelemetry.com
🖥️ macOS/Linux: curl -fsSL https://raw.githubusercontent.com/VasiHemanth/tokentelemetry/main/install.sh | bash
🧰 Windows: irm https://raw.githubusercontent.com/VasiHemanth/tokentelemetry/main/install.ps1 | iex
🐙 GitHub: github.com/VasiHemanth/tokentelemetry
Why TokenTelemetry?
AI coding agents like Claude Code, Gemini CLI, and Codex are powerful — but they burn through tokens fast. How many tokens did that refactor cost? Which agent is most efficient? What did it actually do?
TokenTelemetry answers all of that — locally, instantly, for free.
| Problem | TokenTelemetry Solution |
|---|---|
| "How much did that Claude Code session cost?" | Real-time cost tracking per session/project |
| "What tools did my agent call?" | Full waterfall trace of every tool call |
| "Which model is most token-efficient for my codebase?" | Per-model analytics & comparisons |
| "Did my agent follow its plan?" | Plan-mode capture & display |
| "I use 3 different agents — unified view?" | Multi-agent dashboard in one place |
Supported AI Coding Agents
TokenTelemetry reads session logs from these agents automatically:
| Agent | Status |
|---|---|
| Claude Code (Anthropic) | ✅ Fully supported |
| Gemini CLI (Google) | ✅ Fully supported |
| OpenAI Codex CLI | ✅ Fully supported |
| Cursor | ✅ Fully supported |
| GitHub Copilot | ✅ Fully supported |
| OpenCode | ✅ Fully supported |
| Qwen | ✅ Fully supported |
| Vibe | ✅ Fully supported |
| Antigravity | ✅ Fully supported |
More agents added regularly. Request support for your agent →
Features
- 📊 Token Usage Dashboard — real-time tokens in/out per agent, model, and project
- 💰 Cost Tracking — see exact LLM API costs per session and cumulative over time
- 🔍 Session Traces — waterfall view of prompts, reasoning chains, tool calls, and responses
- 🛠️ Tool Call Analytics — which tools your agents call most, success/failure rates
- 📁 Per-Project Insights — heatmap, activity timeline, agent leaderboard per codebase
- 🧠 Plan Capture — view plan-mode outputs from Claude Code and other agents
- 📈 Model Analytics — compare GPT-5.4 vs Claude 4.6 Sonnet vs Gemini 3.1 Flash efficiency
- 🔒 100% Local — all data stays on your machine, zero cloud dependency
- ⚡ Zero Config — auto-detects agents from their default log locations
- 🆓 Free & Open Source — MIT licensed, forever free
Quick Start
Option 1: One-line installer (recommended)
macOS / Linux:
curl -fsSL https://tokentelemetry.com/install.sh | bash
Windows (PowerShell):
irm https://tokentelemetry.com/install.ps1 | iex
Option 2: Clone & run
git clone https://github.com/VasiHemanth/tokentelemetry.git
cd tokentelemetry
./start.sh # macOS/Linux
# start.bat # Windows
# node bin/cli.js # cross-platform
Option 3: npx (no install)
npx tokentelemetry
Then open: http://localhost:3000
What You'll See
Dashboard
Connected agents, recent activity feed, model distribution pie chart, token burn rate.
Projects View
Per-project heatmap, tool usage breakdown, agent leaderboard, session timeline.
Session Trace
Full waterfall: system prompt → reasoning → tool calls → responses → final output. See exactly what your agent was thinking.
Analytics
Cumulative token & cost graphs per agent/model over time. Compare efficiency across models.
Plans
Captured plan-mode outputs from Claude Code's /plan command and equivalent in other agents.
Requirements
- Node.js 18+
- Python 3.9+
- git
- Any supported AI coding agent already installed (Claude Code, Gemini CLI, Codex, etc.)
Configuration
TokenTelemetry stores lightweight state in ~/.tokentelemetry/:
~/.tokentelemetry/
aliases.json # Rename/merge project folder paths
hidden.json # Hide specific projects from dashboard
VERSION # Current version
All hand-editable JSON — no database, no config GUI needed.
Project Structure
tokentelemetry/
backend/ FastAPI app (Python) — reads agent logs, serves REST API
frontend/ Next.js 16 dashboard — React UI
bin/cli.js Cross-platform launcher
install.sh One-line installer (macOS/Linux)
install.ps1 One-line installer (Windows)
FAQ
Q: Does TokenTelemetry send any data to the cloud?
A: No. 100% local. It reads log files from your filesystem and serves a local web dashboard. Nothing leaves your machine.
Q: How does it track Claude Code token usage?
A: Claude Code writes JSONL session logs to ~/.claude/. TokenTelemetry watches those files and parses token counts, tool calls, and reasoning in real time.
Q: Does it work with multiple agents at the same time?
A: Yes. It detects all supported agents and shows them in a unified dashboard. You can filter by agent, model, or project.
Q: Is there a cost to use TokenTelemetry?
A: No. It is free and open-source under the MIT license.
Q: How is TokenTelemetry different from Langfuse, LangSmith, or Helicone?
A: Those tools require you to instrument your code, create an account, and send data to their cloud. TokenTelemetry is 100% local, zero-config, and works by reading the log files your agents already write — no SDK, no API key, no cloud.
Q: Can I monitor Gemini CLI token usage?
A: Yes. TokenTelemetry supports Gemini CLI and shows token counts, costs, and session traces for Google's Gemini models (Gemini 2.0 Flash, Gemini 1.5 Pro, etc.).
Q: Does it support Cursor or GitHub Copilot?
A: Yes. Cursor and GitHub Copilot sessions are detected and tracked.
Comparisons
| Feature | TokenTelemetry | Langfuse | LangSmith | Helicone |
|---|---|---|---|---|
| 100% Local | ✅ | ❌ | ❌ | ❌ |
| Zero config | ✅ | ❌ | ❌ | ❌ |
| No signup | ✅ | ❌ | ❌ | ❌ |
| Claude Code support | ✅ | Manual | Manual | Manual |
| Gemini CLI support | ✅ | Manual | Manual | ❌ |
| Codex CLI support | ✅ | Manual | Manual | Manual |
| Free | ✅ | Freemium | Freemium | Freemium |
| Open Source | ✅ | ✅ | ❌ | ❌ |
Use Cases
- Individual developers who want to understand how much their AI coding sessions cost
- Teams comparing Claude Code vs Gemini CLI vs Codex efficiency
- Researchers studying LLM agent behavior, tool call patterns, and reasoning chains
- Engineering managers tracking AI tooling ROI across projects
- Prompt engineers optimizing prompts by seeing exact token breakdowns
Troubleshooting
Port conflicts: Check/kill processes on ports 3000 and 8000.
Python not found: Install Python 3.9+ and ensure it's in your PATH.
No sessions showing: Run an agent (Claude Code, Gemini CLI, etc.) first — TokenTelemetry needs existing log files.
Windows issues: Run PowerShell as Administrator for the installer.
Contributing
We welcome contributions! See CONTRIBUTING.md for guidelines.
git clone https://github.com/VasiHemanth/tokentelemetry.git
cd tokentelemetry
# Make your changes
git checkout -b feat/your-feature
git commit -m "feat: your feature"
git push origin feat/your-feature
# Open a Pull Request
Want to add support for a new agent? Open an issue with the agent name and log format.
Related Projects & Keywords
claude-code token usage · gemini cli cost tracking · codex token monitor · AI agent observability · LLM token dashboard · coding agent analytics · local LLM monitoring · token cost calculator · AI coding tool metrics · claude code session viewer · openai codex usage · cursor ide analytics · github copilot usage tracker · LLM observability tool · AI agent telemetry · token usage dashboard open source
License
MIT © 2024 Hemanth Vasi
Author
Hemanth Vasi
🌐 tokentelemetry.com
🐙 github.com/VasiHemanth
💼 LinkedIn
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