MCP Sunucuları

Connects AI agents to Datadog for monitoring, observability, and incident management. Enables querying metrics, viewing traces, searching logs, and managing monitors programmatically. Supports dashboard creation, alert configuration, and SLO tracking through the Model Context Protocol.

MCP server for Grafana's observability platform. Enables AI agents to query metrics from Prometheus, search and analyze logs from Loki, query traces, list and manage dashboards, and investigate incidents. Useful for debugging production issues, building monitoring dashboards, and performing root cause analysis with AI assistance across the full Grafana LGTM stack.

Enables AI agents to interact with Amazon Web Services through the Model Context Protocol. Provides access to core AWS services including S3, Lambda, DynamoDB, CloudWatch, and IAM. Supports resource discovery, log analysis, and infrastructure management with proper credential handling and region awareness.

A powerful, native Go implementation of a Kubernetes MCP server with support for Kubernetes and OpenShift. Unlike kubectl wrappers, it interacts directly with the Kubernetes API server — no external CLI tools required. Distributed as a single lightweight binary for Linux, macOS, and Windows. Supports multi-cluster configurations, Helm chart management, Tekton pipelines, pod exec, log streaming, and optional OpenTelemetry distributed tracing.

Official Docker MCP server for container management. Enables AI agents to list, start, stop, and inspect Docker containers, manage images, view logs, and execute commands inside running containers. Supports Docker Compose operations for multi-container applications and provides container health monitoring capabilities.

Official Heroku MCP server that lets AI agents manage Heroku Platform resources. Supports listing and inspecting apps, scaling dynos, viewing logs, managing config vars and add-ons, and running one-off commands, so deployment and operations tasks can be handled conversationally.

MCP server for the Railway deployment platform. Lets AI agents create projects and services, deploy from repositories, manage environment variables, view deployment logs, and inspect service status. Useful for provisioning backends, databases, and cron jobs and for debugging deploys directly from an AI assistant.

Official CircleCI MCP server. Lets AI agents fetch build and pipeline status, retrieve failed build logs, and diagnose flaky or broken jobs so developers can fix CI failures without leaving their AI-powered tools.

Auth0's official MCP server that connects AI agents to the Auth0 Management API. Lets developers create and configure applications, deploy Actions, manage APIs and connections, and query tenant logs using natural language. Runs locally with interactive tenant authentication and stores access tokens in the system keychain so the model never sees them directly, supporting secure Auth0 administration.

Render's official MCP server for interacting with your Render cloud resources via LLMs. Lets agents list and inspect services, create and manage deploys, read logs and metrics, and query managed Postgres and Key Value instances. Useful for deploying, debugging, and monitoring applications hosted on Render directly from an MCP-compatible assistant.

Official Netlify MCP server for managing web deployments. Lets AI agents create and configure sites, trigger and monitor deploys, manage environment variables, and read build logs. Useful for shipping frontends and serverless functions, debugging failed builds, and automating deployment workflows from an AI assistant.

Official DigitalOcean MCP server for managing cloud infrastructure. Lets AI agents deploy and manage App Platform apps, Droplets, databases, and Spaces object storage, and read logs and metrics. Useful for provisioning and operating cloud resources and debugging deployments through an AI assistant.

MCP server for Jenkins CI/CD. Enables AI agents to trigger builds, inspect job and build status, stream console logs, and diagnose failing pipelines, bringing continuous integration workflows into AI-powered development environments.

Apache SkyWalking's MCP server gives agents access to observability data for tracing, service topology, metrics, logs, and production incident investigation.

BrowserStack's official MCP server for AI-assisted testing. Lets agents manage test cases, run manual and automated tests across real browsers and devices, access debugging artifacts such as logs and session details, and triage failures using plain English. Useful for cross-platform QA and browser-compatibility workflows from MCP-enabled clients.

Dynatrace's official MCP server that brings the Dynatrace observability platform into AI workflows. Lets assistants query problems and vulnerabilities, run DQL against logs, metrics, and traces, inspect entities, and pull real-time monitoring data directly into a developer's coding environment for faster troubleshooting and root-cause analysis.

Official MCP server for DuckDB and MotherDuck. Lets AI assistants run SQL analytics directly against local DuckDB files, in-memory databases, S3-hosted data, and MotherDuck cloud warehouses. Supports read and write queries, browsing database catalogs, and switching between connections on the fly, making it well suited for conversational data exploration and lightweight analytics.

Official Apple Xcode MCP server (xcrun mcpbridge) that gives external AI agents direct access to Xcode IDE capabilities. Provides 20 native tools for building projects, running tests, reading and writing files in the project navigator, searching code with regex, rendering SwiftUI previews, executing code snippets, browsing Apple Developer documentation, and inspecting build logs and workspace issues. Requires Xcode 26+ with MCP enabled in Intelligence settings.