Docker AI Agent Skills

title: System for Cross-domain Identity Management (SCIM) MCP Server colorFrom: pink colorTo: blue sdk: docker appport: 7860 pinned: false shortdescription: SCIM 2.0 relay for AI agents to manage identities - building-mcp-track-enterprise scim-mcp is a SCIM (System for Cross-domain Identity Management) relay for AI agents. This MCP server enables LLMs to manage enterprise user identities and group

MCP server for management and troubleshooting of certificates and other resources managed by cert-manager. Claude Desktop config: Claude Desktop config for GKE clusters: This MCP server provides the following tools for interacting with cert-manager and Kubernetes resources: - listcertificates - List certificates within a namespace or across all namespaces, with options for filtering expired certif

- About the pgEdge Postgres MCP Server - pgEdge Postgres MCP Server - Choosing the Right Solution - Best Practices - Querying the Server - Installing the MCP Server - Quick Start - Quickstart Demo with Northwind - Deploying on Docker - Deploying from Source - Testing the MCP Server Deployment - Configuring the MCP Server - Specifying Configuration Preferences - Using Environment Variables to Speci

Ever wished you could just ask Portainer what's going on? Now you can! Portainer MCP connects your AI assistant directly to your Portainer environments. Manage Portainer resources such as users and environments, or dive deeper by executing any Docker or Kubernetes command directly through the AI. Portainer MCP is a work in progress implementation of the Model Context Protocol (MCP) for Portainer e

Model Context Protocol (MCP) server for InfluxDB 3 integration. Provides tools, resources, and prompts for interacting with InfluxDB v3 (Core/Enterprise/Cloud Dedicated/Clustered/Cloud Serverless) via MCP clients. - InfluxDB 3 Instance: URL and token (Core/Enterprise/Cloud Serverless) or Cluster ID and tokens (Cloud Dedicated/Clustered) - Node.js: v18 or newer (for npm/npx usage) - npm: v9 or newe

An MCP server (stdio transport) that wraps Hugging Face's LocalPythonExecutor (from the smolagents framework). It is a custom Python runtime that provides basic isolation/security when running Python code generated by LLMs locally. It does not require Docker or VM. This package allows to expose the Python executor via MCP (Model Context Protocol) as a tool for LLM apps like Claude Desktop, Cursor

- Requirements - Entity Operations - Telemetry Management - Relations - OTA Packages - Entity Data Query - Quick Start Guide - Installation - Docker Image - Build from Sources - Client Configuration - Binary Configuration - Docker Configuration - Environment Variables - Tool Groups Configuration - Available Tools - Device Tools - Asset Tools - Customer Tools - User Tools - Alarm Tools - OTA Tools

Dependency intelligence infrastructure for AI assistants and agents working with JVM projects. Traditional upgrade workflow: 1. Google "Spring Boot 2.7 to 3.2 migration guide" (5 minutes) 2. Read 50-page migration docs, cross-reference breaking changes (15 minutes) 3. Check Maven Central for compatible dependency versions (5 minutes) 4. Update pom.xml, compile, fix breaking changes (30 minutes) 5.

Act as an expert senior Elixir engineer.

An MCP (Model Context Protocol) server that provides token-efficient access to OpenAPI (v3.0) and Swagger (v2.0) specifications via MCP Resource Templates. The primary goal of this project is to allow MCP clients (like Cline or Claude Desktop) to explore the structure and details of large OpenAPI specifications without needing to load the entire file into an LLM's context window. It achieves this

MCP Server that enables LLMs to interact with the local filesystem. Provides tools for navigation, search, file management, and analysis — all scoped to allowed directories. Filesystem MCP exposes a rich set of tools for reading, writing, searching, and inspecting files and directories. All operations are strictly bounded to the directories you provide at startup, preventing access to any path out

Let MCP clients like Claude and Cursor control Intruder. For more information and sample use cases, please see our blog post. There are two ways to use the MCP server: - Locally on your machine with Python - In a Docker container All of these methods require you to provide an Intruder API key. To generate a key, see the documentation. Install uv if it isn't already present, and then clone this rep

Manage YouTube activities using the yutu CLI. Use this skill when you need to list channel activities such as uploads, likes, and favorites.

� Migrate to MCP Platform • 💬 Discord Community • � Legacy Docs Zero-configuration deployment of production-ready MCP servers with Docker containers, comprehensive CLI tools, and intelligent caching. Focus on AI integration, not infrastructure setup. That's it! Your MCP server is running at http://localhost:8080 Perfect for: AI developers, data scientists, DevOps teams building with MCP. Deploy M

A comprehensive security operations platform that integrates multiple security tools into a unified interface. This platform provides a centralized way to run various security scanning and testing tools. - Unified Interface: Single entry point for multiple security tools - Docker Support: Easy deployment using Docker - JSON Output: Consistent JSON output format across all tools - Error Handling: R

基于 MCP 协议的代码执行器，最后是通过 Docker 来进行代码执行的，所以本机上需要有 Docker 的环境. - [x] 支持 MCP 协议 - [x] 支持代码执行，获得代码执行的结果 - [ ] 获取代码执行的时间、内存等信息

After setup, you can usually just say: The goal is that you only install this MCP server, and it handles the rest (searching servers, selecting servers, configuring servers, etc.). Choose one of the following: 1. Remote (simplest & fastest ⚡💨) 2. Local (prebuilt) — Docker, uvx, or npx 3. Local (from source) — run this repo directly Use the hosted endpoint (recommended for the simplest setup). Doc

Helps configure mcp-rubber-duck MCP server in AI coding tools. Triggers when users ask about adding rubber duck to Claude Desktop, Cursor, VS Code, Windsurf, Continue, or any MCP-compatible tool.

An MCP server for managing Docker with natural language! - 🚀 Compose containers with natural language - 🔍 Introspect & debug running containers - 📀 Manage persistent data with Docker volumes - Server administrators: connect to remote Docker engines for e.g. managing a public-facing website. - Tinkerers: run containers locally and experiment with open-source apps supporting Docker. - AI enthusia

You can run the MCP Server in a Docker container. This is useful if you want to avoid managing Python environments or dependencies on your local machine. See kestramcpdocker. Paste the following configuration into your MCP settings (e.g., Cursor, Claude, or VS Code): - Replace , , and with your actual credentials. - For OSS installations, you can use KESTRAUSERNAME and KESTRAPASSWORD instead of KE

A Node.js server implementing the Model Context Protocol (MCP) for interacting with the storacha.network platform via the w3 command-line interface (@web3-storage/w3cli). This server empowers language models 🤖 and other MCP clients to manage storacha.network spaces, upload/download data, manage delegations, and perform various other tasks by seamlessly wrapping w3 commands. - Wraps the w3 CLI for

A Model Context Protocol (MCP) Server for Lara Translate API, enabling powerful translation capabilities with support for language detection, context-aware translations and translation memories. - 📖 Introduction - 🛠 Available Tools - 🚀 Getting Started - 📋 HTTP Server - 🔌 STDIO Server - 🧪 Verify Installation - 💻 Popular Clients that supports MCPs - 🆘 Support What is MCP? Model Context Proto

Give AI assistants the power to query your Prometheus metrics. A [Model Context Protocol][mcp] (MCP) server that provides access to your Prometheus metrics and queries through standardized MCP interfaces, allowing AI assistants to execute PromQL queries and analyze your metrics data. [mcp]: https://modelcontextprotocol.io - Prometheus server accessible from your environment - MCP-compatible client

A portable, single-binary system auditing tool for Linux. Like Lynis but faster and smarter. No configuration needed. No dependencies. Just run. - 🔒 Security: Firewall, SSH hardening, SSL/TLS, fail2ban, SUID binaries, open ports - 🚀 Services: Systemd services, web servers, databases, Docker - 💻 Resources: CPU, RAM, disk usage, top processes - 💾 Storage: SMART health, inode usage, filesystem er