An MCP server that records agent execution metrics and exposes a Context Window Explorer to visualize exactly what entered the model's context window across sessions, tokens, and tool calls.
MCP server that provides coding agents with structured repository context, including graph-based navigation, dependency analysis, runtime flow tracing, and configuration surface across supported stacks.
This MCP server exposes a local structural code graph and project memory so AI coding agents can retrieve focused code entities, relationships, and prior mistakes before reading full files. It enables bounded context queries, caller/callee and impact analysis, and carryover of recorded session information through a CLI, hooks, and an authenticated local dashboard.
MCP server for AI agent observability, providing trace and span logging, search, latency/tokens/cost metrics, and anomaly detection using an in-memory buffer.
MCP server that reports AI agent costs (tokens, latency, dollars) with per-tenant isolation via OAuth, and includes an ADK agent for natural-language queries.