Discover our curated collection of MCP servers for deployment & devops. Browse 2341servers and find the perfect MCPs for your needs.
Extends applications with AI capabilities via a fast, secure server leveraging WebAssembly plugins.
Simplifies building backend applications in Go with modularity and observability.
Enables AI assistants to interact with Kubernetes clusters through natural language via the Model Context Protocol (MCP).
Simplifies Kubernetes cluster management with an AI-powered, lightweight dashboard featuring multi-cluster support and intelligent analysis.
Provides a secure, sandboxed runtime environment for various programming languages and WASI binaries across browsers, servers, and JavaScript runtimes.
Manage Docker containers using natural language commands.
Enforces Protocol Buffer style and conventions through linting and automated fixes.
Analyzes software composition to extract inventory data, detect vulnerabilities, and generate SBOMs.
Analyzes Java thread dumps and heap information to diagnose performance, deadlocks, and memory issues in Java applications.
Enables MCP-compatible AI agents to deploy applications to Cloud Run.
Facilitates rapid mastery of microservice and distributed project architecture design and development processes.
Generates Model Context Protocol (MCP) servers from OpenAPI specifications, enabling AI agents to interact with existing REST APIs.
Installs and manages Model Context Protocol (MCP) servers, remaining client-agnostic.
Provides an MCP server for programmatically managing n8n workflows.
Manages the lifecycle of Flux CD on Kubernetes, extending it with self-service capabilities and preview environments.
Manage Docker containers and compose stacks through natural language with Claude AI.
Enables AI assistants in Cursor, VS Code, Claude Code, or any MCP-enabled IDE to autonomously manage Home Assistant configurations, automations, dashboards, and themes using natural language.
Manages the lifecycle of plugins for the Dify API server, supporting local, debug, and serverless runtimes.
Manage, govern, and optimize third-party API consumption across applications and AI agent workloads at scale.
Implements a Model Context Protocol (MCP) server for Kubernetes and OpenShift, enabling seamless interaction and management of Kubernetes resources.
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