Splitrail
Splitrail is a fast, cross-platform, real-time token usage tracker and cost monitor for:
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 for safe-keeping and cross-machine usage aggregation. From the team behind 
Piebald.
Download the binary for your platform on the Releases page.
Screenshots
Local Web Dashboard
Run splitrail web and open http://127.0.0.1:8765. Use splitrail web --port 9000 to choose another port. The server listens only on 127.0.0.1 and accepts that IP in the Host header. It reads local usage through the existing analyzers without uploading it. Static assets are embedded in the binary; no frontend build or Node installation is needed to run it.
The overview shows estimated cost, total tokens, replies (model responses), session count, and cache share, with comparisons against the previous period. Filter by today, 7, 30, or 90 days, or all history, and select tools, models, or projects. Selections within one field combine; selections across fields narrow the result. Linked worktrees, repository subdirectories, and paths connected by an analyzer’s project hash are grouped into one project. Hover a project to see its merged paths.
Switch between cost, tokens, and replies, and group the stacked trend by model, tool, or project. The chart supports hourly, daily, weekly, and monthly intervals; click a daily bar to inspect that day by hour. Focus the chart and use the arrow keys to read values, or Enter to drill into a day. Model, tool, and project rankings also filter on click. The five entities with the highest cost in the selected period keep their colors while filters change; the rest are grouped as Other.
Usage snapshots are saved in the system cache directory under splitrail/web-usage-v1.json. On restart, the page immediately shows the saved snapshot while a background scan refreshes it, then updates automatically. The first run without a valid cache waits for a scan. Click Refresh to scan again. Concurrent refreshes share one scan, cached pages remain available during scanning, and a failed refresh preserves the previous snapshot. Cache files with a different application version or timezone are ignored. Dates and hours use the machine’s local time. Total tokens match the TUI: input + output + cached; reasoning tokens are not added again. Costs use public API prices and may differ from subscription spending.
Frontend aggregation tests run with node --test src/web/data.test.mjs.
Model aliases configured in ~/.splitrail.toml also determine dashboard names and grouping, including filters, charts, rankings, and CSV exports. Session details show the original names beneath mapped names. Unmapped models keep their original names. Restart splitrail web after changing aliases; saved snapshots retain the original names and use the current aliases on load.
The Sessions tab provides search, sorting by recency/cost/tokens/replies/active time, and a paginated list. A compact summary shows total active time, replies, cost and tokens per reply, cache share, and project count. Above the list, the session shape card buckets the filtered sessions by reply count, active time, or tool calls, with the median and p90 beside it; the work activity card shows recorded tool calls, file reads, file operations, and shell commands. Active time counts gaps under five minutes between messages, so long idle periods do not inflate session duration. Select a session to see its whole-session totals, reply and tool-call counts, file reads and edits, token mix, per-model replies, tokens, cache share and cost, and its hourly or daily timeline. Shared filters select sessions; the detail panel shows the entire selected session. File and command counts are tool-operation counts, not unique file counts, and are available only where the source analyzer records them.
The Breakdown tab groups the filtered usage by period, project, model, or tool, and includes tool calls, file reads, file operations, and shell commands. Export CSV downloads the same groups, columns, ordering, and total row with exact numeric values. Shares are fractions between 0 and 1; text labels are escaped for spreadsheet use. View and filter selections are kept in the URL hash for bookmarks.
English is the default language; choose Simplified or Traditional Chinese in the header. The preference is saved locally. The dashboard follows the system’s light/dark appearance and adapts to phone widths, with horizontally scrollable charts and tables. Overview also includes a weekday/hour activity heatmap and the largest sessions.
MCP Server
Splitrail can run as an MCP (Model Context Protocol) server, allowing AI assistants to query your usage statistics programmatically.
splitrail mcp
get_daily_stats - Query usage statistics with date filteringget_model_usage - Analyze model usage distributionget_cost_breakdown - Get cost breakdown over a date rangeget_file_operations - Get file operation statisticscompare_tools - Compare usage across different AI coding toolslist_analyzers - List available analyzers
Resources
splitrail://summary - Daily summaries across all datessplitrail://models - Model usage breakdown
Configuration
Splitrail stores its configuration at ~/.splitrail.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
[logging]
level = "warn"
Keeping usage from deleted Piebald chats
Splitrail reads Piebald’s database live, so permanently deleting a chat in Piebald also removes its usage from Splitrail, including from any upload that hasn’t happened yet. To keep counting a chat after you delete it, save a usage archive of it first. The archive is a single file beside Piebald’s database, named after it:
- Linux:
~/.local/share/piebald/app.db.usage-archive (or $XDG_DATA_HOME/piebald/app.db.usage-archive)
- macOS:
~/Library/Application Support/piebald/app.db.usage-archive
- Windows:
%APPDATA%\piebald\app.db.usage-archive
Because it sits beside app.db, whatever copies, backs up, or moves Piebald’s database and its -wal and -shm files can take the archive along too.
An archive is a SQLite file in Piebald’s database layout. Splitrail reads it with the same code it uses for Piebald’s own database and merges the two:
- Each message counts once, even while its chat still exists in Piebald.
- Archived messages keep the date, model, project, price, and identity they had while their chat existed, so they upload to Splitrail Cloud exactly as they would have before the deletion.
- An archive belongs to the database it sits beside. A copy of the database somewhere else uses the archive beside that copy, if there is one.
- An archive that can’t be read is skipped with a warning; it never hides your live usage.
A complete copy of Piebald’s database works as an archive, but it doesn’t need to be one. Splitrail only needs each chat, its messages and their token counts, its tool-call markers, and the profile and project rows they refer to; message text and tool output can be left out. To add chats to an existing archive, write the combined file under another name (such as app.db.usage-archive.partial) and rename it into place when it’s complete, because Splitrail reads the archive each time it refreshes.
Development
Windows
On Windows, we use lld-link.exe from LLVM to significantly speed up compilation, so you’ll need to install it to compile Splitrail. Example for winget:
winget install --id LLVM.LLVM
Then add it to your system PATH:
:: Command prompt
setx /M PATH "%PATH%;C:\Program Files\LLVM\bin\"
set "PATH=%PATH%;C:\Program Files\LLVM\bin"
or
# PowerShell
setx /M PATH "$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:
cargo run
macOS/Linux
Build as normal:
cargo run
License
MIT
Copyright © 2026 Piebald LLC.
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