"Implementing a Local Inpainting Function with Mask Generation Using Canvas" matching MCP servers:

TypeScript stdio MCP server for operating Docker-based local-ydb deployments from AI coding agents. Supports local and SSH-backed profiles, bootstrap, diagnostics, auth hardening, schema permissions, storage workflows, dump/restore, upgrades, and plan-first mutating operations.

Enables AI assistants to interact with local Docker containers, Kubernetes clusters, and system logs using the Model Context Protocol.

MCP server that turns natural-language requests into configured n8n workflows and safely operates a local n8n Docker stack, including workflow management, API access, and Docker lifecycle operations with confirmation-based safety.

Create sandboxed local development environments directly from Github and execute tests, see coverage and more! Supports Python, Node, Bun and many test runners.

Enables Docker container management through natural language conversations, including deployment, health monitoring, dependency resolution, auto-redeployment on file changes, and environment snapshots.

Enables Docker container management and test execution via MCP tools, supporting image building, container operations, and automated test runs.

A VMware ESXi/vCenter management server based on MCP (Machine Control Protocol), providing simple REST API interfaces for virtual machine management.

Provides a local, isolated Linux VM sandbox for AI agents using Apple's Virtualization.framework, enabling fast command execution (~60ms) and package management without cloud costs.

Enables AI assistants to interact with DDEV local development environments by querying databases, managing project states, and executing container commands. It provides comprehensive control over local services with a security-first approach using whitelisted operations.

A Model Context Protocol (MCP) server for running Genesis World simulations with integrated visualization support, using stdio transport to enable local runtime visualization features.

A server implementing Model Coupling Protocol for HDF5 file operations, Slurm job management, hardware monitoring, and data compression.

Enables comprehensive benchmarking and performance monitoring of OpenShift clusters using OVN-Kubernetes networking through automated data collection, AI-powered analysis, and report generation. Provides intelligent insights into cluster performance, bottleneck detection, and optimization recommendations.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

A code-mode MCP server for the Unraid 7.2+ GraphQL API that exposes search and execute tools, allowing LLM agents to introspect and call any GraphQL field via sandboxed JavaScript.

Enables MCP clients to rent GPUs from ParalonCloud using natural language, including browsing available GPUs, starting and stopping rentals, and retrieving connection URLs.

VMware workflow orchestration — multi-step state machine with approval gates, audit logging, and conditional execution. Coordinates cross-skill workflows like clone-and-test or compliance-scan-and-remediate across the VMware MCP skill family.

An MCP server that gives LLM agents full API access to a VMware Cloud Foundation 9.1 estate, exposing 8,931 operations through eight tools with automatic authentication, async task tracking, and write safety.

Install and manage a self-hosted XNS Relayer — S3-compatible distributed object storage — conversationally over stdio. 15 tools cover prerequisites, account registration, install, claim, health, VPD configuration, S3 verification, CLI credentials, settings, restart, and backups.

GenieACS-MCP is a Go-based MCP server that bridges any GenieACS (TR-069 ACS) instance, exposing device data, firmware management, and CPE actions (reboot, parameter refresh, firmware download) over JSON-RPC

A Model Context Protocol server for the resQ emergency response system that integrates with digital twin simulations and coordination engines. It allows users to trigger simulations, generate deployment strategies, and monitor real-time drone status for incident response analysis.