"How to manage and create GitHub Actions workflows" matching MCP servers:

An intelligent MCP server that gives AI agents full control over GitHub Actions CI/CD pipelines, including real-time monitoring, log analysis, AI-powered failure diagnosis, and deployment management.

A minimal MCP server that exposes health-check and server information tools over stdio or HTTP, and can be containerized and deployed to IBM Code Engine.

Monitors and analyzes GitHub repository health by detecting stale branches, old pull requests, unresponsive issues, and security alerts. Integrates with MCP-compatible AI assistants and automation tools.

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.

Enables AI assistants to review workflow status in n8n instances, including active/inactive counts and workflows with recent errors.

Enables real-time assessment of GitHub repository health by exposing tools and resources for repository metadata, open issues, recent commits, and GitHub Actions workflow runs, plus prompts for health reports and issue triage.

Enables agents to look up and search servers from the official MCP registry, probe any server live for availability, protocol, auth, tools and context-token cost, and retrieve registry-wide statistics. Also supplies a CLI and GitHub Action that measure how many tokens your own configured servers' tool definitions consume against a budget.

Enables named, authenticated callers to run read-only introspection of a Google Cloud project and to read and write per-tenant notes that stay isolated between callers. Every request is scope-checked against a reviewed policy, rate-limited per caller, and audited without ever logging argument values.

A pre-action risk gate for AI agents. Your agent calls the forecast tool before any irreversible action — send email, run SQL, make a payment, delete a file — and gets a risk score (0–100) and a GO / CONFIRM / STOP verdict in a few seconds.

An MCP server that retrieves current GitHub Copilot usage data, including quotas, limits, and usage statistics. It allows AI agents to monitor premium interaction status and detailed account usage via raw or formatted summaries.

This server integrates with GitHub Advanced Security to load security alerts and bring it into your context. Supports Dependabot Security Alerts, Secret Scanning Alerts, Code Security Alerts

Enables multi-agent system auditing with seven-layer analysis, cost governance, compliance mapping, and watchdog monitoring. Offers tools for audit execution, cost analysis, report verification, regulation lookup, remediation suggestions, and fix tracking.

Exposes a synthetic issue tracker and pipeline warehouse as callable tools so an agent can answer operational questions about tickets, pipeline health, runs, incidents, and governed metrics with every claim cited to the exact tool call it came from. All writes are proposal-only, requiring human approval through a gated apply path that logs each step for audit.

A comprehensive MCP server providing advanced Redmine project analytics, web automation via Playwright, and iTunes music integration. It enables detailed tracking of sprint metrics, bug counts, and team performance through a token-optimized tool architecture.

Enables users to measure, track, and compare response times of GitHub Copilot and other AI models. Provides statistical analysis and performance comparison tools for evaluating AI model efficiency.

Enables AI agents and users to manage workspace files, monitor system metrics, take persistent notes, and retrieve weather data via MCP tools and resources.

Enables Claude to query and manage Domotz network monitoring through 133 API actions, covering collectors, devices, alerts, and configuration.

A Model Context Protocol (MCP) server for the RIPE Atlas network measurement platform. Enables AI assistants to create network measurements, retrieve results, search probes, and manage credits.

A Model Context Protocol server that gives LLM clients full access to your AppDynamics monitoring data — plus the ability to create and manage dashboards and health rules.

MCP server for Exit1 uptime monitoring. Enables AI assistants to create and manage uptime checks, configure alerts, and query status via natural language.