/mcp
Guide for working with Splitrail's MCP server. Use when adding tools, resources, or modifying the MCP interface.
$ npx -y skills add Piebald-AI/splitrail --skill mcp --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/mcp
Context preview
The summary Claude sees to decide when to auto-load this skill.
Guide for working with Splitrail's MCP server. Use when adding tools, resources, or modifying the MCP interface.
SKILL.md
mcp.SKILL.mdname: mcp description: Guide for working with Splitrail's MCP server. Use when adding tools, resources, or modifying the MCP interface.
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
- `splitrail://summary` - Daily summaries across all dates
- `splitrail://models` - Model usage breakdown
Adding a New Tool
1. Define the tool handler in `src/mcp/server.rs` using the `#[tool]` macro 2. Add request/response types to `src/mcp/types.rs` if needed
See existing tools in `src/mcp/server.rs` for the pattern.
Adding a New Resource
1. Add URI constant to `resource_uris` module in `src/mcp/server.rs` 2. Add to `list_resources()` method 3. Handle in `read_resource()` method
Splitrail is a fast, cross-platform, real-time token usage tracker and cost monitor for: Gemini CLI (and Qwen Code) Claude Code Codex CLI Cline / Roo Code / Zoo Code / Kilo Code (VS Code extension + CLI) GitHub Copilot (VS Code) GitHub Copilot CLI OpenCode Pi
Repo: Piebald-AI/splitrail
Other skills on splitrail.
- /new-analyzer
Guide for adding a new AI coding agent analyzer to Splitrail. Use when implementing support for a new tool like Copilot, Cline, or similar.
Open skill - /performance
Performance optimization guidelines for Splitrail. Use when optimizing parsing, reducing memory usage, or improving throughput.
Open skill - /pricing
Guide for updating model pricing in Splitrail. Use when adding new AI model costs or updating existing pricing data.
Open skill - /tui
Guide for Splitrail's terminal UI and file watching. Use when modifying the TUI, stats display, or real-time update logic.
Open skill - /types
Reference for Splitrail's core data types. Use when working with ConversationMessage, Stats, DailyStats, or other type definitions.
Open skill

