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

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    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.
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    Apache 2.0
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    Enables AI assistants to review workflow status in n8n instances, including active/inactive counts and workflows with recent errors.
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    MIT
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    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.
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    MIT
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    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.
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    MIT
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    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
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    MIT
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    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.
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    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.
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    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.
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    MCP server for monitoring health of MCP servers, GitHub Actions, GitLab pipelines, and HTTP endpoints with health history, TLS expiry, assertions, diagnostics, and alerts.
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    MIT
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    Enables AI agents to manage a Canonical Landscape estate, including inventory, alerts, patching, and script execution, with built-in safety layers to prevent accidental destructive actions.
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    MIT
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    Enables AI assistants to interact with and manage Kubernetes clusters, supporting operations on pods, deployments, services, configmaps, secrets, namespaces, metrics, and events with built-in safety features for destructive actions.
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    MIT
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    Enables LLM agents to monitor and manage a Proxmox VE cluster, including cluster status, VM/container lifecycle, and node actions via MCP tools.
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    MIT
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    Run NRQL, NerdGraph, and REST v2 operations to query data, manage incidents, create synthetics, and annotate deployments — all from your MCP client.
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    MIT
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    Connects AI assistants to the Vectra AI security platform to enable intelligent analysis of threat detection data and automated incident response workflows. It allows users to investigate threats, take response actions, and generate security reports using natural language.
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    MIT