"How to view Shopify order and product selling details" matching MCP servers:

MCP server enabling AI agents to trace and resolve order synchronization incidents between an ERP (Odoo) and multiple marketplaces.

Connects Shopify's Liquid profiler to AI assistants to diagnose slow themes, providing performance reports and recommendations without editing the live theme.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

Enables AI assistants to interact with Rollbar error tracking and monitoring service, allowing them to diagnose issues, view item details, list deployments, retrieve session replays, and update item properties through natural language commands.

Connects AI assistants to IonHour uptime monitoring workspaces to manage projects, monitoring checks, and incident responses. It enables users to view reliability metrics, send heartbeats, and manage status pages through natural language.

An MCP-native enterprise operations platform that unifies team management, product catalog, order processing, knowledge base, location intelligence, analytics, and DevOps monitoring into a single server accessible from any MCP-compatible AI agent.

Enables AI assistants to interact with Healthchecks.io, allowing users to list, create, update, pause, resume, and delete checks, as well as view ping history and integrations.

Enables coding agents to debug backend requests by providing tools to list, view, wait for, diagnose, and clear request traces.

Analyzes how search engines and AI systems discover, crawl, cite, and convert traffic via CLI and MCP tools.

Enables AI to automatically perform Root Cause Analysis for app issues (e.g., sessions not recording, heatmap empty, replica drift) by querying logs, MongoDB, Shopify, and rendering rrweb replays.

Exposes read-only Order Orchestrator diagnostics, including search_order_failure_logs backed by live telemetry from Render.

MCP server for analyzing Ascend PyTorch Profiler performance data. Enables users to identify performance bottlenecks, analyze operator time, view communication overhead, and query trace data via natural language.

An AI Operations Investigation MCP server that enables LLMs to investigate order fulfillment incidents by correlating data across independent services using predefined scenarios.

An MCP server for querying Grafana Loki directly with a discovery-first workflow — labels, values, series, and LogQL queries without requiring Grafana.

Enables querying logs and metrics with plain SQL from any MCP client via pooml's read-only query API.

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.

Provides cryptographically signed, tamper-evident compute usage receipts via a Model Context Protocol server, exposing tools to record usage, verify receipts, list the ledger, and verify ledger integrity without requiring any account, API key, or single cloud provider.