### Check out Piebald We've released **Piebald**, the ultimate agentic AI developer experience. \ Download it and try it out for free! **https://piebald.ai/** Join our Discord X [**Scroll down for Splitrail.**](#splitrail) :point_down:
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# Splitrail Splitrail is a **fast, cross-platform, real-time token usage tracker and cost monitor for**: - [Gemini CLI](https://github.com/google-gemini/gemini-cli) (and [Qwen Code](https://github.com/qwenlm/qwen-code)) - [Claude Code](https://github.com/anthropics/claude-code) - [Codex CLI](https://github.com/openai/codex) - [Cline](https://github.com/cline/cline) / [Roo Code](https://github.com/RooCodeInc/Roo-Code) / [Kilo Code](https://github.com/Kilo-Org/kilocode) (VS Code extension + CLI) - [GitHub Copilot](https://github.com/features/copilot) (VS Code) - [GitHub Copilot CLI](https://github.com/features/copilot) - [OpenCode](https://github.com/sst/opencode) - [Pi Agent](https://github.com/badlogic/pi-mono/tree/main/packages/coding-agent) Run one command to instantly review all of your CLI coding agent usage. Upload your usage data to your private account on the [Splitrail Cloud](https://splitrail.dev) for safe-keeping and cross-machine usage aggregation. From the team behind [ **Piebald.**](https://piebald.ai/) > [!note] > ⭐ **If you find Splitrail useful, please consider [starring the repository](https://github.com/Piebald-AI/splitrail) to show your support!** ⭐ **Download the binary for your platform on the [Releases](https://github.com/Piebald-AI/splitrail/releases) page.** ## Screenshots ### [Splitrail CLI](https://splitrail.dev) Screenshot of the Splitrail CLI ### [Splitrail VS Code Extension](https://splitrail.dev) Screenshot of the Splitrail VS Code Extension ### [Splitrail Cloud](https://splitrail.dev) Screenshot of Splitrail Cloud ## MCP Server Splitrail can run as an [MCP (Model Context Protocol)](https://modelcontextprotocol.io/) server, allowing AI assistants to query your usage statistics programmatically. ```bash splitrail mcp ``` ### Available Tools - `get_daily_stats` - Query usage statistics with date filtering - `get_model_usage` - Analyze model usage distribution - `get_cost_breakdown` - Get cost breakdown over a date range - `get_file_operations` - Get file operation statistics - `compare_tools` - Compare usage across different AI coding tools - `list_analyzers` - List available analyzers ### Resources - `splitrail://summary` - Daily summaries across all dates - `splitrail://models` - Model usage breakdown ## Configuration Splitrail stores its configuration at `~/.splitrail.toml`: ```toml [server] url = "https://splitrail.dev" api_token = "your-api-token" [upload] auto_upload = false upload_today_only = false [formatting] number_comma = false number_human = false locale = "en" decimal_places = 2 ``` ## Development ### Windows On Windows, we use `lld-link.exe` from LLVM to significantly speed up compilation, so you'll need to install it to compile Splitrail. Example for `winget`: ```shell winget install --id LLVM.LLVM ``` Then add it to your system PATH: ```cmd :: Command prompt setx /M PATH "%PATH%;C:\Program Files\LLVM\bin\" set "PATH=%PATH%;C:\Program Files\LLVM\bin" ``` or ```pwsh # PowerShell setx /M PATH "$env:PATH;C:\Program Files\LLVM\bin\" $env:PATH = "$env:PATH;C:\Program Files\LLVM\bin\" ``` Then use standard Cargo commands to build and run: ```shell cargo run ``` ### macOS/Linux Build as normal: ``` cargo run ``` ----- ## License [MIT](https://github.com/Piebald-AI/splitrail/blob/main/LICENSE) Copyright © 2026 [Piebald LLC](https://piebald.ai).