"Best practices for organizing and structuring a codebase" matching MCP servers:

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.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

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.

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

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.

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.

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.

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

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.

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

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

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

Connects LLMs to Google PageSpeed Insights to analyze web performance, accessibility, SEO, and best practices, enabling AI assistants to audit and improve any web page.

Enables AI agents to diagnose Linux server incidents by collecting and structuring system diagnostics from multiple servers via SSH, with tools for finding incident clusters, gathering context (memory, CPU, swap, etc.), and running arbitrary commands.

MCP server for Kibana / Elasticsearch — log search, aggregations, index discovery, and dashboard browsing. Hits Elasticsearch REST API directly for log queries; falls back to Kibana Console proxy when no direct ES URL is configured. Supports ApiKey auth (best for agents), Basic auth, and anonymous access. All 5 tools are read-only (readOnlyHint: true). Returns structured JSON (outputSchema).

A lightweight server that provides real-time system information including CPU, memory, disk, and GPU statistics for monitoring and diagnostic purposes.

A Model Context Protocol (MCP) server for PostgreSQL that provides safe, structured access to your database for AI assistants, enabling health checks, index tuning, lock analysis, and more.