A local-first MCP server that gives AI coding agents runtime visibility and AI-managed debug logging. It replaces blind print() debugging by turning runtime execution into causal chains, allowing agents to instantly locate bugs by finding missing .success events in Python and TypeScript code. Single binary with MCP, CLI, and HTTP interfaces.
A read-only MCP server that exposes local coding-agent session logs as three tools for introspection of recent work, debugging tool failures, and tracking token usage and estimated cost without parsing log files.
Enables debugging of distributed transactions by continuously ingesting Docker container logs, indexing them by trace/request ID, and exposing MCP tools to search, tail, and correlate logs across services.
An MCP server that enables coding agents to log their work, decisions, test runs, PRs, and progress as structured events, either to a local JSONL file or an HTTP endpoint.
Enables coding agents to use a real debugger (Python via debugpy) for launching, attaching, setting breakpoints, stepping through code, inspecting stack frames, and evaluating expressions through MCP tools.
