// Guide for working with Splitrail's MCP server. Use when adding tools, resources, or modifying the MCP interface.
| name | mcp |
| description | Guide for working with Splitrail's MCP server. Use when adding tools, resources, or modifying the MCP interface. |
Splitrail can run as an MCP server, allowing AI assistants to query usage statistics programmatically.
cargo run -- mcp
src/mcp/mod.rs - Module exportssrc/mcp/server.rs - Server implementation and tool handlerssrc/mcp/types.rs - Request/response typesget_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 analyzerssplitrail://summary - Daily summaries across all datessplitrail://models - Model usage breakdownsrc/mcp/server.rs using the #[tool] macrosrc/mcp/types.rs if neededSee existing tools in src/mcp/server.rs for the pattern.
resource_uris module in src/mcp/server.rslist_resources() methodread_resource() methodGuide for adding a new AI coding agent analyzer to Splitrail. Use when implementing support for a new tool like Copilot, Cline, or similar.
Performance optimization guidelines for Splitrail. Use when optimizing parsing, reducing memory usage, or improving throughput.
Guide for updating model pricing in Splitrail. Use when adding new AI model costs or updating existing pricing data.
Guide for Splitrail's terminal UI and file watching. Use when modifying the TUI, stats display, or real-time update logic.
Reference for Splitrail's core data types. Use when working with ConversationMessage, Stats, DailyStats, or other type definitions.