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。2051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。
Monitors and logs running processes, making their output and status accessible to AI agents through the Model Context Protocol.
Enables AI assistants like Claude to interact with Databricks workspaces by hosting Model Context Protocol (MCP) prompts and tools on Databricks Apps.
Exposes Databricks functionality as a Model Completion Protocol (MCP) server, enabling LLM-powered tools to interact with Databricks resources.
Provides a Vercel-deployable template for building custom Model Context Protocol servers with extensible functionalities.
Establishes a Model Context Protocol server on Cloudflare Workers, providing secure OAuth-enabled access for AI clients to custom tools.
Deploys an authentication-free Model Context Protocol (MCP) server on Cloudflare Workers for AI agent tool integration.
Demonstrates the development and execution of serverless functions using Netlify Functions, with a focus on integrating Model Context Protocol.
Enables interaction with a Python interpreter and file system within a Docker container environment.
Provides stateful, interactive terminal access for persistent processes and command-line interactions.
Manages intelligent research data using vector embeddings and semantic search for saving, organizing, and retrieving content, deployed on AWS EC2.
Manages Windows processes and services by offering AI-assisted and direct command-line interfaces for secure discovery, inspection, and control with integrated UAC elevation.
Provides an AI-agent-driven server with a Gradio UI for penetration testing and purple team operations.
Integrate natural language interfaces with Railway.app infrastructure for service deployment, variable management, and monitoring.
Empower AI models like Claude to securely and intuitively manage Docker containers using the Model Context Protocol.
Provides a foundational Model Context Protocol server for demonstrating custom tools, resources, and prompts.
Enables AI agents to dynamically collect user input through automatically generated web forms based on provided field names.
Manages an AWS Aurora Postgres server configured with the Pgvector extension.
Establishes a foundational server environment developed with Python.
Provides SSH functionality for managing remote servers, executing commands, and performing file operations.
Validates GitHub operation execution through a server integration.
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