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AI EngineeringRust

Splitrail MCP

by Piebald-AI

Splitrail MCP is an AI Engineering skill for Claude Code, published by Piebald-AI in splitrail.

217 stars25 forkson Piebald-AI/splitrailAdded 2026/09/04Repository updated 2026/09/03
View source on GitHubDownload repo ZIP
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Install in seconds
Install Splitrail MCP
Copy Splitrail MCP into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.
terminal
npx degit https://github.com/Piebald-AI/splitrail/tree/main/.claude/skills/mcp ~/.claude/skills/mcp

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/Piebald-AI/splitrail.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file
.claude/skills/mcp/SKILL.md in Piebald-AI/splitrail
Installs to
~/.claude/skills/mcp
Collection
One of 6 skills cataloged from this repository
Category
AI Engineering — 2970 skills

What Splitrail MCP does

Splitrail MCP lets AI assistants query usage statistics, model breakdowns, cost data, and file operation counts through an MCP server. Use it when adding or modifying tools and resources for the interface.

Splitrail MCP is cataloged under AI Engineering on DirSkills. Splitrail MCP comes from a repository tagged agentic, analyzer, antigravity-cli, blazing-fast and ccusage.

Documentation

README

MCP Server

Splitrail can run as an MCP server, allowing AI assistants to query usage statistics programmatically.

cargo run -- mcp

Source Files

  • src/mcp/mod.rs - Module exports
  • src/mcp/server.rs - Server implementation and tool handlers
  • src/mcp/types.rs - Request/response types

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

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Splitrail MCP

  • What else does Piebald-AI publish alongside Splitrail MCP?

    Splitrail MCP is one of 6 skills that DirSkills catalogs from Piebald-AI/splitrail, the repository it ships in. Its siblings there include New Analyzer, Performance and Pricing. Each one is a separate skill with its own page in this directory, installs the same way Splitrail MCP does, and is maintained by Piebald-AI in that same repository. The rest of the collection is listed on the Piebald-AI/splitrail page.

  • How does Splitrail MCP compare to other AI Engineering skills?

    Splitrail MCP ranks #2624 by stars among the 2970 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Splitrail MCP against them. Open each page to compare what they document and how they install.

More from Piebald-AI/splitrail

Splitrail MCP is one of 6 skills cataloged on DirSkills from Piebald-AI/splitrail.

See all 6 skills →
🧩
2h ago

New Analyzer

New Analyzer guides adding support for a new AI coding agent analyzer in Splitrail. Use it when implementing parsing for a tool like Copilot, Cline, or another agent with its own data files.
AI Engineering
21725
⚡
2h ago

Performance

Performance provides guidelines for optimizing Splitrail code. Use it when improving parsing, reducing memory usage, or increasing throughput.
Quality
21725
💲
2h ago

Pricing

Pricing guides updating model cost data in Splitrail. Use it when adding new AI models, aliases, caching rules, or dated pricing overrides.
AI Engineering
21725
🖥️
2h ago

TUI

TUI guides Splitrail's terminal interface, live stats updates, and file watching. Use it when changing the TUI, stats display, or real-time update logic.
Frontend
21725
🧩
2h ago

Types

Types is a reference for Splitrail's core data structures. Use it when working with ConversationMessage, Stats, DailyStats, hashing, or daily aggregation.
Data
21725

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AI-First Engineering

AI-First Engineering defines process, review, and architecture standards for teams where AI agents produce most implementation output. Use it to set ownership rules, quality gates, and evaluation criteria for agent-generated code.
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Agentic OS

Agentic OS codifies a persistent multi-agent operating system architecture for Claude Code. Use it when building a multi-agent workflow with file-based memory, slash commands, and scheduled automation that survives session restarts.
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