"A guide to managing GitLab projects" matching MCP servers:

Enables AI agents to monitor and debug GitLab CI/CD pipelines by providing tools to list pipelines, retrieve job logs, and analyze failure root causes. It features automated error pattern extraction and failure analysis to streamline pipeline troubleshooting.

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.

Enables managing multiple Microsoft Clarity projects by routing requests per client name using a token map, proxying the official Clarity MCP server with tools to list and switch clients.

MCP server for monitoring health of MCP servers, GitHub Actions, GitLab pipelines, and HTTP endpoints with health history, TLS expiry, assertions, diagnostics, and alerts.

Provides a Model Context Protocol server to integrate Vercel API for managing projects, deployments, environment variables, and domains.

MCP Server for notify to telegram / weixin

Enables automated access to LoadRunner Cloud APIs for retrieving performance test data, managing projects, and collecting test results. Supports integration with AI clients for building performance engineering workflows and dashboards.

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 MCP clients to triage SOC alerts while enforcing a trust firewall across retrieval, memory, and privileged actions. It exposes tools for alerts, logs, memory, and alert actions, with defenses that refuse risky operations in the presence of attacker-controllable content.

A local MCP server for managing SaaS projects with planning, operations, and secrets, designed to work with Claude Code via stdio. It provides tools for kanban, health monitoring, and secure secrets management, all logged for AI transparency.

Enables querying and managing Sentry projects, issues, and events through natural language.

Automates three core workflows for Sangfor Engineer: project all-in-one (Excel to guide to validation to report), equipment health check, and Obsidian wiki integration.

Enables MCP clients to inspect Google Play releases, reviews, Android vitals, and scoped bulk reports, and to prepare explicitly authorized changes using locally supplied service-account credentials. Reads are default, while optional writes and sensitive reads require explicit configuration and single-use execution.

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.

A lightweight MCP server that enables AI assistants to execute local development tools and retrieve system status with low latency over stdio or HTTP.

MCP server for system monitoring, enabling users to ask about CPU, memory, disk, network, and processes on their system.

Web analytics and AI session replay for agents: visitors, breakdowns, funnels, goals, revenue attribution, and AI-found site issues. Connects to the hosted Flowsery MCP server.

Enables AI agents to discover and call Xyte's device management API endpoints with typed validation, supporting fleet investigation, ticket management, and routine operations through natural language.