"MCP to Enable Agents to Use OpenRouter or Google Vertex API" matching MCP servers:

Runtime access for AI coding agents to observe and control Android and iOS apps.

Enables tracing mcp-use tool callbacks and capturing tool errors and exceptions in Sentry via MCP middleware, without SDK changes or additional services.

An MCP server that enables interaction with Google Cloud Logging API, allowing users to write, read, and manage log entries and configurations through natural language.

Enables natural language queries of the Chrome UX Report API to fetch Core Web Vitals (LCP, INP, CLS, FCP, TTFB), compare form factors, benchmark pages against site averages, and analyze up to 40 weeks of performance trends.

Monitors API endpoint health by checking availability, measuring response times, and providing detailed status reports with error handling and timeout protection for the localhost:8080/api/ticket endpoint.

Enables endpoint availability monitoring and HTTP health checks for single or multiple URLs.

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

Monitor and manage Apache Airflow clusters through natural language queries via MCP tools: DAG inspection, task monitoring, health checks, and cluster analytics without API complexity. * Guide: https://call518.medium.com/mcp-airflow-api-a-model-context-protocol-mcp-server-for-apache-airflow-5dfdfb2

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 unified local API gateway providing caching, rate limiting, and full Model Context Protocol compatibility for AI agent integration. It enables users to aggregate multiple API endpoints into a single gateway with built-in observability and customizable eviction strategies.

Enables AI assistants to search, analyze, and debug application API traffic captured by Tusk Drift, including HTTP requests, database queries, distributed traces, latency metrics, and error rates.

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

Data observability for AI agents. Query alerts, monitor freshness, investigate schema drift, and trace lineage across your data warehouse via 53 MCP tools.

Enables AI assistants to search Elasticsearch logs, retrieve log details, analyze service health, scan local codebases for APIs, and create Kibana dashboards.

Monitor the real-time status of 200+ popular APIs and services. Check if services like GitHub, Stripe, AWS, and Slack are experiencing outages or degraded performance directly from your AI assistant.

Provides tools and context for interacting with Google Cloud services, enabling natural language management of billing, monitoring, logging, IAM, Spanner, and more.

Provides secure access to the LogicMonitor API, enabling AI assistants to manage monitoring infrastructure through natural language commands.

Enables LLM clients to manage Uptime Kuma HTTP(S) monitors, groups, tags, and notifications, and to retrieve heartbeats, stats, and incident history through MCP tools.

Enables AI assistants to query, search, and analyze logs across Google Cloud Platform projects. It supports advanced filtering by severity or resource type and provides detailed log entry retrieval and project listing capabilities.

Enables AI agents to explore and, when writes are enabled, modify a Langfuse deployment — traces, observations, sessions, prompts, datasets, scores, metrics and more — through the full Langfuse public API. Supports Langfuse Cloud in any region and self-hosted instances, including corporate networks that re-sign TLS traffic with their own certificate authority.