Discover our curated collection of MCP servers for deployment & devops. Browse 3425 servers and find the perfect MCPs for your needs.
Manages `.clinerules` files through reusable components and persona templates with version tracking.
Executes command-line operations through the Model Context Protocol (MCP).
Enables querying of AWS resources using boto3 code snippets via a Model Context Protocol (MCP) server.
Enables sending various types of messages to DingDing group robots via an MCP server.
Executes k6 load tests via the Model Context Protocol (MCP).
Facilitates AI-driven diagnostics and insights for Rollbar error tracking and monitoring.
Enables AI assistants to interact with Helm repositories and charts by providing a standardized way to access chart information and values.
Enables AI agents to query, discover, and analyze Prometheus metrics through natural language interactions via a unified interface.
Scans and remediates hardcoded secrets in codebases using GitGuardian's API, detecting over 500 secret types.
Provides an AI-powered interface for debugging and inspecting Kubernetes clusters with eBPF-based gadgets.
Empowers AI agents to execute, optimize, and manage JavaScript/TypeScript projects using the Bun runtime via Model Context Protocol.
Enables AI assistants to securely access Kernel platform tools and perform low-latency cloud-browser automation.
Enables AI assistants to interact with Salesforce organizations by providing tools for Apex execution, data querying, metadata management, and code analysis via the Salesforce CLI.
Exposes Ansible utilities and workflows through an Advanced Model Context Protocol (MCP) server.
Enables AI coding assistants to interact with JetBrains TeamCity CI/CD server, providing natural language control over builds, tests, and deployments.
Spawns ephemeral Linux sandbox containers using Docker to execute commands via an interactive TTY interface, enabling collaborative AI and human interaction.
Connect Lenses, a DataOps platform for Apache Kafka, to various client applications via the Model Context Protocol.
Orchestrates multiple AI models for automated code review, security analysis, and multi-agent consensus within development workflows.
Automates the Unity Editor with artificial intelligence, providing direct control over Unity objects and workflows.
Provides a self-hosted code execution sandbox platform for individuals and small teams.
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