"How to create and edit edge functions on Supabase" matching MCP servers:

An MCP server that exposes Runloop Devbox operations as tools, enabling AI agents to create and manage Linux sandboxes, execute commands, edit files, snapshot disks, and drive interactive PTY sessions.

Provides tools to list, create, power on/off, and delete VMs on vCenter or ESXi hosts using natural language.

Enables AI assistants to run shell commands, read, write, edit, search, and stream files on remote SSH servers and Docker containers, including nested multi-layer chains, without installing any runtime on the target hosts. It auto-injects a self-contained Go helper with adaptive zstd compression for fast transfers and process control.

MCP server for managing Yandex Cloud infrastructure including Compute VMs, Object Storage, Serverless Functions, and Operations.

Enables AI coding agents to manage cloud containers, create and edit files, run commands, and deploy projects directly.

A remote MCP bridge that lets MCP clients use Modal sandboxes for Linux execution, dependency installation, Git operations, GPU jobs, and invoking deployed Modal Functions.

Enables AI assistants such as Claude, Gemini, and GPT to connect directly to VMware ESXi and vCenter hosts over stdio JSON-RPC. Provides full virtual machine lifecycle management (create, clone, delete, power on/off) plus real-time CPU, memory, storage, and network performance monitoring, with API key authentication and SSL/TLS support.

Enables natural-language onboarding, deployment, and management of edge nodes and their per-node MCP servers, including skill installation, app deployment, and fleet-wide tool calls over SSH.

An MCP server to create secure code sandbox environment for executing code within Docker containers.

Enables AI agents to create, drive, checkpoint, reset and delete resettable Windows and Ubuntu desktop VMs on Apple Silicon Macs, giving them real desktops to click, type and screenshot in plus shell commands, file transfer and port forwarding. All processing is local, so agents can work in isolated guests without leaving the Mac.

Enables administering VMware ESXi or vCenter hosts through MCP clients, exposing tools to authenticate, list, create, clone, power on and off, and delete virtual machines, and to retrieve VM performance statistics. Supports both native SSE and Streamable HTTP transports for integration with current MCP clients.

Enables AI coding agents to create disposable, isolated Firecracker MicroVM sandboxes on AWS Lambda, execute commands, transfer files, and tear them down when done.

Enables users to create, inspect, list, and delete per-user JupyterLab servers on the UChicago ATLAS Analysis Facility Kubernetes cluster, with GPU availability and supported image listing tools.

Enables AI assistants to read, create, and edit Proxmox LXC container and VM Notes through MCP tools, with a preview and snapshot before every write so changes stay reversible.

Enables coding agents to deploy Next.js apps and provision Postgres, Redis, MinIO, NATS, Mailpit, and nginx locally via Docker without requiring Vercel or Supabase signups, using a single account and reading logs from the same environment.

Connects AI assistants to NVIDIA Jetson Nano systems for edge computing management, enabling natural language control of AI workloads, hardware optimization, and system administration tasks.

Enables MCP clients to create, update, destroy, and list Vagrant (VirtualBox) VMs on a remote host through natural-language tool calls over Streamable HTTP, handling fixed-IP allocation, Vagrantfile rendering, and Ansible-based configuration. Its provisioner architecture allows other infrastructure backends such as Terraform or public clouds to be added without changing existing code.

Provisions Docker-based development environments on demand, allowing AI agents to create, manage, and inspect containerized dev environments without manual setup.

Lets AI agents manage local virtual machines: create macOS and Linux VMs on Apple silicon and WSL distros on Windows, start/stop, clone, back up, and run commands inside them.

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 an AI agent to view and control VMware vSphere VM consoles—screen, mouse, and keyboard—through vCenter, without installing anything in the guest.

Enables AI agents to inspect pending updates and service health for Proxmox VE VMs and containers, then take snapshots, apply official updates, reboot, and roll back under tag-based permissions and human-confirmed risky actions.

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

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.

Enables AI coding agents to safely run commands, install dependencies, test, and modify code inside disposable, policy-enforced Docker sandboxes isolated from the host, returning results and diffs.

Enables systematic investigation of VMware errors and events by correlating event timelines, ranking root-cause hypotheses, and suggesting next diagnostic steps.

VMware vSphere compliance and hardening — read-only baseline scanning plus drift detection across CIS, DISA STIG, vSphere SCG, China DJCP 2.0, and PCI-DSS frameworks. Includes LLM-powered remediation suggestions; apply-side gated through the vmware-pilot approval workflow.

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.