# Containerization

The MCP Server is a server that provides AI assistants with the ability to perform web searches and access web pages, supporting the secure acquisition of real-time information and the processing of web page content.

A headless Gmail server that provides email sending and receiving functions through the MCP protocol

Model Context Protocol Daemon is a tool for managing MCP servers, supporting functions such as quick installation and multi - instance management.

Configuration for building and running test projects using Docker

MCP service deployment project based on Kubernetes

Grasp is an open-source and self-hostable humanized browser automation tool that supports the MCP and A2A protocols and can seamlessly integrate with various AI applications. Through Docker containerization deployment, it provides a browser operation experience controlled by natural language.

Configuration example for running the MCP server through Docker containers

An implementation of the MCP protocol by Selector AI, providing real-time interactive AI services

An MCP server based on the R language, providing ggplot2 data visualization and R script execution functions, supporting multiple output formats and Docker containerized operation.

A simple calculator service based on a custom model context protocol (MCP), supporting basic arithmetic operations and deployed via Docker containers.

Posuer is a powerful MCP protocol manager that serves as a bridge between LLM clients and multiple MCP servers, providing containerized isolation, dynamic configuration reloading, multi-server capability aggregation, and intelligent routing.

A Docker management server based on the Model Context Protocol that provides container management functions through a natural language interface

A lightweight MCP server implementation that exposes custom tools via SSE for AI client integration.

The AWS Boto3 MCP Server is a Python-based MCP service designed to monitor and manage AWS account resources by executing code through the Boto3 client of the AWS Python SDK. The service uses a front - end MCP server and a back - end AWS LightSail container architecture and ensures security by requiring the client to provide valid AWS credentials.

This project provides Docker configuration for containerized operation of the Salesforce MCP server.

An MCP server project based on Spring Boot that exposes the OWASP ZAP security tool as an MCP protocol service for AI agents to call the scanning function.

This project is the Kubernetes deployment configuration for the Model Context Protocol (MCP) service, including the Docker image building, Azure Container Registry pushing, and K8s cluster deployment processes, and supports health checks, monitoring, and security protection.

Automated MetaTrader 5 trading strategy optimization and documentation generation system

The MCP Secure Installer is an automated tool for installing and containerizing MCP servers from GitHub repositories, supporting multi - server management.

MCP Obsidian Docker is a containerized Obsidian server that interacts with Obsidian through the Local REST API plugin, providing a convenient note management interface.

This is an MCP server implementation project based on SearXNG, providing privacy - protected search capabilities for AI agents. The project is deployed through Docker containerization, supports two transport protocols, SSE and Stdio, and can be easily integrated into MCP - compatible clients.

A prototype of the MCP tool that generates method stubs based on OpenAPI Schema, supporting containerized deployment

The OWASP ZAP MCP server is a protocol server that integrates the Zed Attack Proxy security scanning tool with an AI assistant. It supports multiple scan types and containerized deployment, enabling shift-left security testing in development.

The Octopus Deploy MCP server is an interactive tool based on the MCP protocol, providing functions for project management, version release, and deployment management, and supporting multi-space operations and Docker containerized deployment.

The MCP server provides infrastructure connection services for LLM agents, supporting interaction with databases, file storage, Kafka, and web interfaces. It is deployed in a containerized manner and integrated with Gitlab Agent and LLM Chat to achieve automated data pipeline creation

The WildFly MCP project aims to provide WildFly users with tools to monitor and manage servers using generative AI capabilities, including components such as MCP servers, chatbots, container images, and protocol gateways.

The MCP server based on pyATS enables structured network device interaction through the JSON-RPC 2.0 protocol

This is an MCP server project that provides a standardized interface for the Polymarket prediction market. It supports deployment through Docker containers and provides functions such as market data query, event information acquisition, and order book viewing, making it convenient for AI assistants to analyze prediction markets.

BaseMcpServer is a basic Docker - based MCP server image that provides a standardized Python environment and protocol support for quickly building and deploying MCP services.

A multi - functional computing and monitoring toolset based on JBang and the MCP server