"Resources for Full Stack Development with Beautiful UI" matching MCP servers:

A Model Context Protocol server that provides AI assistants access to AWS CloudWatch Logs, enabling browsing, searching, summarizing, and correlating logs across multiple AWS services.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

Enables AI agents to interact seamlessly with Splunk environments through 20+ tools for search, analytics, data discovery, administration, and health monitoring. Features AI-powered troubleshooting workflows and supports multiple Splunk instances with production-ready security.

MCP servers for real-time development monitoring and interactive pair programming.

Enables querying and analyzing Falco security events from Falcosidekick UI through MCP tools. Supports filtering events by time windows and retrieving full event details for security monitoring and incident investigation.

Enables AI-driven SOC investigations by providing automated Splunk querying, threat intelligence enrichment, and response actions through natural language. Includes tools for IP pivoting, lateral movement detection, and label harvesting.

A Model Context Protocol server that provides seamless integration with Coroot observability platform, enabling monitoring of applications, analysis of performance metrics, examination of logs and traces, and management of infrastructure through Coroot's comprehensive API.

An MCP server implementation that integrates AI assistants with Langfuse workspaces, allowing models to query LLM metrics by time range.

Provides a standardized way for MCP clients to interact with Apache Airflow's REST API, supporting operations like DAG management and monitoring Airflow system health.

MCP server that integrates with VictoriaMetrics vmanomaly API to enable AI-assisted anomaly detection, model management, and configuration generation.

Enables AI clients like Claude to triage, investigate, and operate Icinga installations through natural language, integrating with Icinga's REST APIs and providing deep awareness of monitoring plugins and historical performance data.

Enables an AI assistant to diagnose a broken application on a local Kubernetes cluster by inspecting pods, events, and logs, with server-side guardrails, least-privilege RBAC, and an audit log. It can also restart deployments in allowed namespaces only after a dry-run preview and host approval.

A safety layer and monitoring copilot for AI agents using Splunk MCP, recording tool calls, enforcing policies, and blocking risky actions.

Enables natural language analysis of network packet captures, including protocol detection, flow analysis, and security threat identification, integrated with AI assistants.

Provides tools to search Splunk logs, inject test data, and send triage emails, enabling AI-driven incident investigation.

MCP server for integrating self-hosted Sentry with AI assistants, enabling project and issue listing, issue details with stack traces, and event retrieval.

MCP server for self-hosted Sentry instances, providing tools to query and triage issues and events, inspect stack frames, manage releases, and access raw Sentry API.

MCP server for Langfuse that lets Claude Code create projects, manage API keys, and query traces without touching the web UI. Designed to work with a self-hosted Langfuse v3 stack running locally via Docker Compose.

Enables read-only, stack-aware diagnostics for microservices on Kubernetes, turning debugging runbooks into conversational tools that investigate slow requests, changes, leaks, and in-pod conditions without exposing cluster credentials.

MCP server giving AI assistants full control of a Proxmox homelab, enabling management of VMs, containers, Docker projects, media stack, and monitoring via natural language.