"A guide to interface components in UI design" matching MCP servers:

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.

An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

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

Enables AI agents to monitor Docker containers, system resources, ports, and logs in real-time.

Enables AI assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.

A server that enables AI assistants to access and query Grafana dashboards, metrics, logs, and configurations through an MCP protocol interface.

A Model Context Protocol server that provides tools to interact with Matomo Analytics API, enabling management of sites, users, goals, segments, and access to analytics reports through a MCP interface.

Provides access to Consul functionality (services, health checks, KV store, sessions, events, queries, etc.) through a standardized Model Context Protocol interface.

Read-only MCP server for TrueNAS Scale debugging, providing k3s tools for kubectl operations and whitelisted midclt calls for system info, apps, and pools.

InfluxDB-v1-MCP is a powerful Model Context Protocol (MCP) interface specifically designed for InfluxDB v1.x, enabling AI assistants to intelligently manage and query time-series databases.

Provides read-only, multi-vendor network device interaction, configuration auditing against vendor-guide rules, and safe diffing of proposed changes for AI agents to inspect and analyze network infrastructure without any commit or write capability.

The MCP server provides an interface to the Datadog API, enabling seamless management of incidents, monitoring, logs, dashboards, metrics, traces, and hosts. Its extensible design allows easy integration of additional Datadog APIs for future expansions.

Enables monitoring and querying of Datadog metrics for Kubernetes clusters, APM traces, infrastructure hosts, and databases through a unified interface.

Enables real-time Kubernetes cluster observability and debugging through standardized MCP interface. Provides access to pods, services, nodes, events, and includes built-in tools for cluster health analysis and issue identification.

Streams live React profiler data to AI agents, enabling them to analyze performance and suggest specific, actionable fixes for slow components.

Provides a read-only interface to Kubernetes clusters, enabling LLMs to list pods, get pod status and logs, fetch deployment manifests, and perform pod health analysis with resource trend tracking.

A Model Context Protocol server that provides comprehensive tools for monitoring and identifying performance bottlenecks in Logstash instances through an interactive web UI and JSON-RPC interface.

An MCP server for querying Grafana Loki directly with a discovery-first workflow — labels, values, series, and LogQL queries without requiring Grafana.

An MCP server that records agent execution metrics and exposes a Context Window Explorer to visualize exactly what entered the model's context window across sessions, tokens, and tool calls.

Provides cryptographically signed, tamper-evident compute usage receipts via a Model Context Protocol server, exposing tools to record usage, verify receipts, list the ledger, and verify ledger integrity without requiring any account, API key, or single cloud provider.