"An analytics platform for tracking and understanding website and app performance" matching MCP servers:

Enables Claude/Lyra to create, monitor, and manage live sessions for long-running operations such as downloads, conversions, and agent jobs, with progress metrics, logs, error alerts, and a Textual dashboard; it also ingests updates from external media-server tools.

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.

A comprehensive, AI-powered performance analysis and monitoring platform for OpenShift/Kubernetes clusters. This project provides Model Context Protocol (MCP) servers for analyzing etcd, network, and OVN-Kubernetes components with deep performance insights, automated root cause analysis, and actionable recommendations.

A Python-based MCP server that analyzes PostgreSQL query plans, suggests indexes, and checks pagination safety to help optimize database performance.

A read-only MCP server that enables AI agents to act as GCP platform engineers, allowing them to investigate incidents, take inventory, and find cost-optimization opportunities in Google Cloud projects without mutating any infrastructure.

Read-only MCP server that exposes Kubernetes platform state (tenants, pods, SLOs, ArgoCD applications, chaos schedules, and catalog services) to AI agents, enabling natural language queries about cluster health and configuration.

A security-first MCP server for Umami analytics (Cloud and self-hosted v3) enabling analytics, reporting, and administration with least privilege and credential-safe design.

Enables AI agents to debug and repair historical Solaris/SPARC systems by providing an out-of-band control plane with guest DTrace, QEMU monitor access, SPARC-aware GDB, host eBPF/perf tracing, and an immutable evidence ledger for cross-layer hypothesis testing.

Lets AI assistants read cookieless website analytics and manage goals, alerts, and uptime checks through a hosted MCP endpoint with permission-scoped access tokens.

Read-only PostgreSQL analytics MCP server — query plans, slow queries, index usage, table bloat, vacuum status. No DDL/DML/writes. Curated by Archimedes Market with a verified Trust Report.

A production-grade MCP server for Couchbase Enterprise Analytics, exposing 25 tools to execute SQL++ queries, manage schema and indexes, configure links, and monitor cluster health.

Lets your coding agent talk to the RunWhen platform — workspace chat, issues, SLXs, run sessions, and the Tool Builder — over the Model Context Protocol. Enables workspace chat with AI assistant, task authoring via Tool Builder, and direct data access to workspaces, issues, SLXs, run sessions, and more.

Enables MCP hosts like ChatGPT and Claude to query data platform metadata, explore schemas and tables, inspect SQL explain plans, and monitor DAG and ETL status through standardized tools.

An MCP server implementation for accessing Google Analytics 4 (GA4) data, built using the Model Context Protocol TypeScript SDK.

Tracks and analyzes AI agent tool calls with event logging, dashboard, per-tool and per-agent analytics, and error monitoring.

Enables AI agents to query Google Analytics 4 data, including listing accounts and properties, running historical and real-time reports with customizable metrics and dimensions.

A Model Context Protocol server that enables AI agents to query Azure Log Analytics workspaces using KQL.

Enables tracing every tool call from a ChatGPT app into LangSmith, one run per tool call, grouped per conversation thread. Provides thread-level evaluation and monitoring of tool interactions.

Enables querying privacy-focused website analytics from Plausible's read-only Stats API v2, with tools for overview, timeseries, breakdown, and goal performance metrics.

A framework for building MCP servers with built-in enterprise capabilities such as authentication, authorization, telemetry, audit logging, and data classification, allowing domain developers to focus on business logic while maintaining governance and compliance.