"Writing about MCP" matching MCP servers:

Gives Claude live access to your Observe tenant, enabling natural language queries about errors, logs, and metrics without writing OPAL pipelines.

Provides Claude with read-only access to PC diagnostics including hardware specs, live performance metrics, disk usage, network checks, and more, enabling natural language queries about PC health and performance.

The policy enforcement plane for MCP: deterministic admission and egress policy, attributable audit, and SIEM export for your MCP server fleet. Self-hosted and MIT licensed.

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.

MCP server that provides read-only analysis of Claude Code session transcripts, enabling queries about project activity, session details, and tool usage.

MCP server exposing qbit_manage's Web API as tools, so an LLM can read and manage a qbit_manage instance: run maintenance commands on qBittorrent torrents, manage config files, scheduler, logs, security settings, and system state.

Enables LLM agents to query real-time and historical analytics from WireBoard, allowing natural language questions about visitors, events, and site metrics.

Enables AI agents to push and read metrics from EzStat, track counters/gauges, and ask natural-language questions about telemetry.

Provides AI agents with real-time ground truth about what's actually running on the machine, including live agent sessions, listening TCP ports, loaded daemons, and system stats. It reads directly from the OS via fixed commands, ensuring agents never rely on stale docs or transcripts.

Connects AI assistants to Crontinel, enabling natural language queries about cron jobs, queues, Horizon status, and alerts without opening a browser.

An MCP server that enables AI agents to safely operate multi-cluster Kubernetes fleets through an Open Cluster Management hub, with policy enforcement, human approval, and audit tracing.

Read-only MCP server that exposes Kubernetes platform state (tenants, pods, SLOs, ArgoCD applications, chaos schedules, and catalog services) to AI agents, enabling natural language queries about cluster health and configuration.

Enables LLMs to query telemetry data via the Spyglass AI agent, providing intelligent insights about application performance, errors, and bottlenecks.

MCP server for Minecraft modpack diagnostics, enabling mod conflict detection, log/crash analysis, and dependency lookup via Modrinth.

The AgentOps MCP server provides access to observability and tracing data for debugging complex AI agent runs. This adds crucial context about where the AI agent succeeds or fails.

An MCP server for managing multiple OpenShift Container Platform (OCP) clusters through AI assistants.

Enables AI assistants to interact with and manage Google Cloud Platform resources including Compute Engine, Cloud Run, Storage, BigQuery, and other GCP services through a standardized MCP interface.

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.

A Model Context Protocol server that provides AI agents with controlled read access to Datalust Seq instances for log analysis and monitoring. It enables agents to search events, execute data queries, and retrieve information about signals, dashboards, and alerts.

A comprehensive, AI-powered performance analysis and monitoring platform for OpenShift/Kubernetes clusters. This project provides Model Context Protocol (MCP) servers for analyzing etcd, network, and OVN-Kubernetes components with deep performance insights, automated root cause analysis, and actionable recommendations.