Browse all content tagged with DevOps
The Azure DevOps MCP Server acts as a bridge between natural language requests and the Azure DevOps REST API, enabling AI assistants and tools to automate DevOps workflows, manage work items, and access project/team information directly from conversational interfaces.
Debugg AI MCP Server offers AI-driven browser automation and end-to-end UI testing for web applications. Integrate with FlowHunt or CI/CD pipelines to automate UI testing, simulate user behavior, and analyze visual output, all via natural language or CLI tools.
The n8n MCP Server enables seamless integration between AI assistants and the n8n automation platform, allowing FlowHunt users to trigger, monitor, and manage automated workflows using AI agents.
The Prefect MCP Server bridges AI assistants and the Prefect workflow orchestration platform, enabling natural-language management of flows, deployments, runs, and more. Easily automate, monitor, and control Prefect resources through FlowHunt or other AI-powered interfaces.
The snyk-ls MCP Server bridges AI assistants and development workflows with Snyk’s security tools, enabling code vulnerability scanning, security findings management, and contextual security recommendations directly within development environments through the Model Context Protocol (MCP).
The Unleash MCP Server bridges AI assistants and LLM applications to the Unleash Feature Toggle system, enabling automated feature flag management, project discovery, and dynamic feature exposure for AI-driven workflows.
Alibaba Cloud Ops MCP Server enables seamless integration with Alibaba Cloud APIs, empowering AI agents to automate resource management, monitoring, and DevOps workflows through standardized Model Context Protocol interfaces.
The AWS Resources MCP Server lets AI assistants manage and query AWS resources conversationally using Python and boto3. Integrate powerful AWS automation and management into your FlowHunt workflows with secure, permission-based operations.
The Cloudflare MCP Server bridges AI assistants and Cloudflare’s cloud services, enabling natural language automation for configurations, logs, builds, and documentation. Easily integrate Cloudflare’s APIs and observability into AI-powered workflows with secure, robust setup.
The Cronlytic MCP Server brings seamless AI-powered automation to serverless cron job infrastructure, enabling LLMs to manage, monitor, and optimize scheduled tasks through a unified Model Context Protocol (MCP) interface.
The GitHub Actions MCP Server empowers AI assistants to manage GitHub Actions workflows, automate CI/CD tasks, analyze workflow runs, and enhance security in software development pipelines.
Integrate and automate Grafana’s dashboards, datasources, and monitoring tools into AI-driven development workflows using FlowHunt's Grafana MCP Server. Enable seamless AI-powered dashboard management, query execution, and observability integration.
The Helm Chart CLI MCP Server bridges AI assistants and the Helm package manager for Kubernetes, enabling natural language automation of Helm workflows such as chart installation, repository management, and command execution. Boost developer productivity and streamline Kubernetes operations by exposing Helm’s capabilities to AI-driven tools.
The k8s-multicluster-mcp MCP Server provides seamless, centralized management of multiple Kubernetes clusters via a standardized API, supporting resource operations, context switching, and cross-cluster comparisons for AI workflows and developer teams.
The Kong Konnect MCP Server integrates AI assistants with Kong Konnect's API Gateway, enabling natural language queries for analytics, configuration, and control plane management through standardized Model Context Protocol (MCP) tools.
MCP Discovery is a Rust-based command-line tool that automates the discovery and documentation of MCP Server capabilities, tools, and resources. It generates comprehensive, up-to-date documentation in Markdown, HTML, or text formats for seamless integration into developer workflows and CI pipelines.
The mcp-server-docker MCP Server enables AI assistants to manage Docker containers through natural language. Integrate this MCP with FlowHunt and other clients for automated container orchestration, introspection, debugging, and persistent data management.
The Raygun MCP Server bridges AI assistants and Raygun's robust API, enabling automated error management, deployment tracking, performance monitoring, source map handling, and team management within FlowHunt workflows.
The Terminal Controller MCP Server enables secure execution of terminal commands, directory navigation, and file system operations through a standardized interface. It bridges AI assistants and host environments, empowering automation and safe management of system-level tasks.
Integrate AI assistants with the Terraform Cloud API using the Terraform Cloud MCP Server. Manage infrastructure through natural language, automate workspace and project tasks, and streamline infrastructure-as-code workflows, all from your favorite AI platforms.
The Windows CLI MCP Server bridges AI assistants with Windows command-line interfaces and remote systems via SSH, providing secure, programmable command execution and automation for local and remote environments.
The 1Panel MCP Server bridges AI assistants and the 1Panel management platform, enabling automation, secure remote operations, and real-time AI integration for system administration workflows.
Integrate Apache Airflow into your FlowHunt workflows with the Apache Airflow MCP Server. This bridge enables AI agents to manage, monitor, and automate Airflow DAGs through a standardized protocol, unlocking seamless workflow orchestration, monitoring, and dynamic pipeline management.
The AWS Cost Explorer MCP Server connects AI assistants like Claude with AWS Cost Explorer and Bedrock Model Invocation Logs, enabling natural language queries and analysis of cloud spend data for enhanced AWS cost management and reporting.
The Consul MCP Server bridges AI assistants and developer tools with HashiCorp Consul’s powerful service discovery, health checking, and key-value store APIs. This integration empowers AI-driven workflows to automate infrastructure management, real-time monitoring, event handling, and dynamic configuration in Consul-powered environments.
The Dynatrace MCP Server connects the Dynatrace observability platform to your AI-powered workflows in FlowHunt, enabling real-time access to production metrics, logs, anomalies, and security events for enhanced debugging, monitoring, and automation.
The Honeycomb MCP Server bridges AI assistants and Honeycomb observability data, enabling LLMs to securely analyze metrics, dashboards, and code behavior for enterprise workflows. It automates data analysis, accelerates root cause investigation, and streamlines SLO management within developer operations.
The LaunchDarkly MCP Server connects AI assistants and agents with LaunchDarkly’s feature management platform via the Model Context Protocol, enabling automated feature flag management, environment configuration, rollout orchestration, and workflow automation from within AI-powered tools.
The Nomad MCP Server bridges AI assistants and HashiCorp Nomad, enabling real-time orchestration, job management, and infrastructure automation directly from FlowHunt workflows and other AI tools.
The Phone MCP Server is a plugin for the Model Context Protocol (MCP) that enables remote control of Android devices using ADB commands. It bridges AI assistants and Android devices for automation, management, and real-time interactions, empowering workflows that require direct physical device access.
The Pinner MCP Server for FlowHunt enables automated, secure pinning of Docker base images and GitHub Actions to immutable digests, enhancing supply chain security and reproducibility in development workflows.
Rust MCP Filesystem is a blazing fast, asynchronous, and lightweight MCP server written in Rust, enabling secure and efficient filesystem operations for AI-assisted workflows. It offers advanced glob search, read-only safety by default, and seamless integration with FlowHunt and other development tools.
The Terraform MCP Server connects FlowHunt and AI agents to the Terraform Registry, enabling automated discovery, extraction, and analysis of Terraform providers, modules, and resources for advanced Infrastructure as Code workflows.
The WildFly MCP Server connects WildFly servers to generative AI tools, enabling natural language management and monitoring of WildFly environments through FlowHunt. Automate server operations, streamline troubleshooting, and integrate with AI-driven workflows for efficient server administration.
The Atlassian MCP Server bridges AI assistants with Atlassian tools like Jira and Confluence, enabling automated project management, documentation retrieval, and enhanced software development workflows within FlowHunt.
The CircleCI MCP Server bridges CircleCI’s powerful CI infrastructure with the MCP ecosystem, enabling AI assistants to automate and monitor workflows, access build analytics, and streamline development pipelines directly from FlowHunt.
MCP Create is a dynamic server management service that allows on-demand creation, execution, and orchestration of multiple MCP servers. Designed for scalable, modular AI workflows, it enables developers to launch, update, and manage MCP servers programmatically, supporting robust tool execution and lifecycle management.
The mcp-k8s-go MCP Server enables AI assistants to interact programmatically with Kubernetes clusters via Model Context Protocol, automating and streamlining DevOps workflows through a standardized interface.
The Multicluster MCP Server empowers GenAI systems and developer tools to manage, monitor, and orchestrate resources across multiple Kubernetes clusters via the Model Context Protocol (MCP), enabling intelligent automation and streamlined DevOps workflows.
ssh-mcp-server is a secure Model Context Protocol (MCP) server that enables AI assistants and development tools to safely execute SSH commands and transfer files on remote servers, all without exposing credentials. Ideal for remote management, deployment automation, and file synchronization in your FlowHunt workflows.
The System Health MCP Server for FlowHunt enables real-time remote Linux server monitoring—exposing CPU, memory, disk, network, and security metrics to AI assistants via the Multi-Channel Protocol. Automate infrastructure health checks, receive threshold-based alerts, and streamline DevOps workflows with direct AI integration.
The Vantage MCP Server bridges AI assistants and MCP clients with your cloud cost data, enabling natural language querying and analysis of cloud spend through Vantage's APIs. Easily analyze, forecast, and manage cloud expenses for AWS, Azure, GCP, and more.
The Codacy MCP Server bridges AI assistants with the Codacy platform, enabling automated code quality, security analysis, repository management, and developer workflow optimization through programmatic access to Codacy’s robust API.
The Confluent MCP Server empowers AI assistants to interact with Confluent Cloud APIs, enabling natural language management of Kafka topics, connectors, and Flink SQL jobs for streamlined, automated streaming data operations.
The Heroku MCP Server bridges AI assistants with the Heroku platform, enabling automated app management, deployments, resource monitoring, and configuration via standardized Model Context Protocol (MCP) tools. Integrate Heroku into your AI-driven workflows for streamlined cloud automation.
Integrate your AI assistants with the JFrog Platform API using the JFrog MCP Server. Automate repository management, build tracking, runtime monitoring, artifact search, and vulnerability analysis for enhanced DevOps workflows.
The JMeter MCP Server bridges Apache JMeter with AI-driven workflows, enabling automated performance testing, analysis, and seamless integration in development pipelines. It exposes JMeter’s features as tools and resources for modern, AI-enhanced engineering environments.
The Keycloak MCP Server enables AI-powered management of Keycloak users and realms through a Model Context Protocol (MCP) interface, automating administrative tasks such as user creation, deletion, realm and user listing for streamlined DevOps workflows.
The Kibana MCP Server bridges AI assistants with Kibana, enabling automated search, dashboard management, alert monitoring, and reporting through the standardized Model Context Protocol for powerful, AI-driven workflows.
The Kubernetes MCP Server bridges AI assistants and Kubernetes/OpenShift clusters, enabling programmatic resource management, pod operations, and DevOps automation through natural language workflows.
The Kubernetes MCP Server bridges AI assistants and Kubernetes clusters, enabling AI-driven automation, resource management, and DevOps workflows through standardized MCP commands.
The KubeSphere MCP Server enables AI assistants and LLM development tools to seamlessly manage KubeSphere clusters, automating tasks such as workspace, cluster, user, and extension management to boost cloud-native development and DevOps workflows.
The MCP Containerd server bridges Containerd's runtime with the Model Context Protocol (MCP), enabling AI agents and automation workflows to manage containers, pods, and images programmatically. It empowers DevOps and AI-driven environments with robust container lifecycle and image management through standardized endpoints.
MCP-NixOS is a Model Context Protocol server for NixOS, enabling AI assistants and developers to programmatically access and manage NixOS configurations, packages, and system state. It streamlines infrastructure automation, reproducible builds, and AI-powered DevOps workflows.
ntfy-mcp is an MCP server that acts as a notification bridge between AI assistants and the ntfy notification service, enabling real-time task completion alerts and streamlined development workflows.
The Postman MCP Server enables AI assistants to execute Postman collections and automate API testing workflows using Newman, all via a standardized MCP interface. Integrate API validation, environment management, and granular test reporting seamlessly into your AI-driven QA flows.
The Prometheus MCP Server enables AI assistants to interact with Prometheus metrics using standardized Model Context Protocol (MCP) interfaces. It supports PromQL queries, metric discovery, metadata access, and time-series analytics for automated monitoring and AI-driven infrastructure insights.
The Pulumi MCP Server enables AI assistants and development tools to manage cloud infrastructure programmatically by bridging Pulumi’s infrastructure-as-code platform with the Model Context Protocol (MCP). Streamline deployments, automate updates, and control cloud resources directly from your favorite AI-powered environments.
The RabbitMQ MCP Server enables AI assistants to manage, automate, and interact with RabbitMQ message brokers through the Model Context Protocol (MCP). It streamlines queue management, broker administration, and dynamic message operations for robust distributed systems—fully integrated with FlowHunt workflows.
Integrate powerful, programmatic email-sending capabilities into your AI workflows with the Resend MCP Server. Seamlessly connect AI agents to the Resend email API for automating notifications, transactional emails, and workflow communications.
