deployment & devops向けの厳選されたMCPサーバーコレクションをご覧ください。3455個のサーバーを閲覧し、ニーズに最適なMCPを見つけましょう。
Facilitates the creation of MCP servers using Go.
Enables LLMs and AI Agents to manage serverless cron jobs through CRUD operations via the Cronlytic API.
Establishes a secure connection between GitHub and VS Code through a Dockerized Model Context Protocol (MCP) server.
Integrates an MCP server directly as an asynchronous task within a Tokio runtime.
Integrates Azure DevOps services into AI chat interfaces, enabling direct task management and information retrieval.
Provides a smart, real-time command execution system for Kali Linux, adhering to the Model Context Protocol (MCP) standard.
Provides a custom Databricks server to test Model Context Protocol (MCP) integrations and On-Behalf-Of (OBO) authentication.
Demonstrates RESTful CRUD operations and Object-Relational Mapping (ORM) for JSON objects using the Gilhari microservice framework.
Provides Model Context Protocol tools for unified message queue management across Redis Streams, RabbitMQ, and NATS.
Provides programmatic access to systemd journal logs, enabling advanced querying and filtering capabilities.
Provides a Model Context Protocol interface for UniFi Network Controller, enabling AI assistants and other clients to manage network infrastructure.
Provides persistent memory, real-time AI-to-AI communication, and a federation mesh for multi-agent AI systems.
Enables runtime creation, management, and execution of tools for AI agents and operators in isolated Docker sandboxes.
Integrates Greenbone/OpenVAS (GVM) vulnerability management capabilities and orchestrates scans via the Model Context Protocol, enabling LLM/agent interaction.
Orchestrates deployment workflows for AI agents, enabling them to manage static website deployments and Supabase migrations to your own AWS account.
Enables AI assistants to interact with zkSync smart contracts and development tools through a comprehensive set of CLI commands.
Executes and orchestrates shell commands with advanced background job management and observability features.
Enables AI assistants to execute a wide range of administration actions on Jira Data Center instances via the Model Context Protocol.
Control and automate your RunCloud server infrastructure through conversational AI, performing tasks from deployment to monitoring.
Analyzes git history to provide advanced code intelligence, predicting change impact and detecting potential bugs with high accuracy.
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