Tools and platforms for comprehensive system observability including logs, metrics, and traces. Enables monitoring, troubleshooting, and performance analysis of applications and infrastructure.
EU-hosted website monitoring + 17-framework compliance MCP. One anonymous tool, four authenticated.
290+ quality-scored API capabilities for AI agents across 27 countries via MCP.
Connect engineering metrics, DORA performance, and deploy risk scoring to any AI assistant. Score PRs for deployment risk using a 36-signal model, query team health, incidents, coverage, and more.
Service level agreement monitoring for the Hive agent fleet
Enable secure connectivity between Sentry issues and debugging data, and LLM clients, using a Model Context Protocol (MCP) server.
Free MCP tools: the only MCP linter, health checks, cost estimation, and trust evaluation.
performance-review MCP — wraps StupidAPIs (requires X-API-Key)
The Google GKE MCP server is a managed Model Context Protocol server that provides AI applications with tools to manage Google Kubernetes Engine (GKE) clusters and Kubernetes resources. It exposes a structured, discoverable interface that allows AI agents to interact with GKE and Kubernetes APIs, enabling them to inspect cluster configurations, retrieve Kubernetes resource YAMLs, monitor operations like cluster upgrades, diagnose issues, and optimize costs—all without needing to parse text output or use complex kubectl commands.
Gain visibility into the performance, availability, and health of your apps and infrastructure.
Live status, API pricing and rate limits for ChatGPT, Claude, Gemini, Cursor and 42+ AI tools.
ThousandEyes MCP Server for network intelligence: outages, anomalies, alerts, events, and tests.
Enterprise AI governance: spend, guardrails, policy, budgets, compliance, and provider health.
RUM platform for web performance analytics, Core Web Vitals, and third-party script monitoring.
Real-time health monitoring and heartbeat tracking for agent services
The Cortex MCP server provides read-only access to real-time engineering context from the Cortex developer portal, allowing AI coding assistants to answer natural language questions about your organization's catalog (microservices, libraries, domains, teams, infrastructure), scorecards (engineering standards and best practices), initiatives (goals and deadlines), and Engineering Intelligence metrics. It includes tools for querying documentation, tracking personal entities, and accessing AI-assisted insights across the entire Cortex ecosystem.
Read-only MCP server for AIStatusDashboard status, incidents, metrics, and fallback recommendations.
Data observability tools for engineering teams: alerts, freshness, schema drift, lineage, quality.
The Buildkite MCP server exposes Buildkite product data (pipelines, builds, jobs, and test data) to AI tools, editors, and agents through the Model Context Protocol. It provides capabilities including pipeline creation and management, build monitoring with specialized tools like 'wait_for_build', efficient log querying using Apache Parquet conversion and caching, and OAuth-based authentication for both read-write and read-only access to Buildkite's REST API.
