mcp

Guide for working with Splitrail's MCP server. Use when adding tools, resources, or modifying the MCP interface.

$ 安裝

git clone https://github.com/Piebald-AI/splitrail /tmp/splitrail && cp -r /tmp/splitrail/.claude/skills/mcp ~/.claude/skills/splitrail

// tip: Run this command in your terminal to install the skill


name: 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