deployment & devops를 위한 엄선된 MCP 서버 컬렉션을 찾아보세요. 3455개의 서버를 탐색하고 필요에 맞는 완벽한 MCP를 찾아보세요.
Connect functions across different languages and network boundaries to AI agents.
Integrate with the Datadog API to manage incidents, monitors, logs, dashboards, metrics, traces, and hosts.
Enables operations on AWS resources, including S3 and DynamoDB, through the Model Context Protocol.
Enables interaction with Kubernetes clusters through Model Control Protocol (MCP) tools.
Exposes Portainer environment data through the Model Context Protocol (MCP), enabling AI assistants to interact with containerized infrastructure.
Enables efficient handling of filesystem operations through a fast and asynchronous MCP server.
Enables seamless integration of VictoriaMetrics with Model Context Protocol (MCP) clients for enhanced monitoring, observability, and debugging.
Facilitates the development and testing of MCP servers by acting as both a server for Claude and a client for servers under test.
Deploys a custom remote server to the cloud using Azure Functions for use with the Model Context Protocol.
Packages an Express server and the MCP SDK into an executable file.
Enhances Proxmox virtualization management with complete OpenAPI integration and advanced VM lifecycle control.
Enables AI assistants to interact with and manage Azure Kubernetes Service (AKS) clusters.
Orchestrates AI coding agents like Claude Code CLI and Gemini CLI to automate and manage complex coding tasks.
Deploy intelligent multi-agent swarms and coordinate autonomous workflows in an advanced agentic development environment.
Orchestrates multiple MCP tools on-demand, drastically reducing token usage for AI agent contexts.
Implements a blazingly fast gRPC client and server in Zig, prioritizing maximum performance and minimal overhead.
Offers a unified AI development environment providing file operations, code execution, web deployment, data processing, and image generation for comprehensive agent capabilities.
Simplifies Kubernetes cluster creation, maintenance, and operation across various distributions and providers through a single CLI.
Diagnose and resolve compatibility issues within NVIDIA GPU, CUDA, and AI software stacks across local, containerized, and CI/CD environments.
Orchestrates multiple AI coding agents declaratively to automate software development workflows for engineering teams.
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