"Node-RED" matching MCP servers:

Enables MCP clients to control an infra-TAK host, including marketplace modules, Node-RED flows, MediaMTX video, TAK video publishing, and Docker operations via local APIs.

Domain security reconnaissance for AI agents — 13 tools (DNS+DNSSEC, SSL/TLS, HTTP security headers, SPF/DKIM/DMARC email auth, port scan, ASN, RDAP/WHOIS) plus a one-shot security_scan returning a 0–100 Health Score (A–F). Free, no API key.

MCP server for controlling PNETLab v6 network labs via natural language, enabling topology creation, node management, config push, console interaction, and link fault injection.

Enables AI agents to query Oracle WebLogic Server runtime state, health, and JVM metrics through the REST management API, and to start, shut down, or force-shut-down servers via Node Manager, all under a least-privilege account with allowlisting, read-only mode, and JSON audit logging for every call.

A Model Context Protocol server that exposes a MeshCore node and the mesh reachable through it as a clean, high-signal interface for AI agents or tools.

MCP server for managing a Marzban proxy/VPN panel — full user, subscription, node, host, and config lifecycle through 21 tools and 3 investigation prompts. Enforces env-only credentials, profile-gated tool visibility (readonly/standard/full), and a confirmation-token gate on every destructive call.

MCP server for controlling EVE-NG network emulator instances via REST API, enabling lab/node/network management, topology editing, and device operations through natural language.

MCP server for FreeIPA / Red Hat IdM — user, group, host, DNS, HBAC, and sudo management via the Model Context Protocol.

Visual network topology editor with AI agent integration via MCP. One-click SSH + web-service access from any node, nmap/CSV import, smart auto-layout, multi-sheet, local-first. Open-source successor to netViz (CA Technologies 1990-2012)

MCP server for Cisco Modeling Labs (CML) that enables building, managing, and running network labs through MCP tools, wrapping the CML Python SDK for lab/topology CRUD, node/link management, and configuration.

Enables AI assistants to discover devices and perform connectivity diagnostics across a private Tailscale or WireGuard mesh through authenticated CLI or REST API backends. Supports safe dry-run simulations before affecting live node state.

Enables red-team and blue-team security workflows on BlackArch Linux by wrapping local tools like nmap, gobuster, nikto, and hydra as MCP tools, with scope-gating that prevents unauthorized scanning against any target not explicitly listed in a local scope.yaml file.

Enables AI assistants to manage Proxmox VE infrastructure, including VMs, containers, storage, network, high availability, replication, SDN, and node administration.

Enables managing Nginx Proxy Manager resources like proxy hosts, redirection hosts, streams, access lists, certificates, users, and settings through MCP, with automatic JWT refresh and configurable transport modes.

Enables deploying apps, managing servers, domains/DNS, VPS lifecycle, and account balance on Impreza Host via AI in VS Code.

Enables LLM clients to ask natural-language questions about FABRIC Testbed infrastructure metrics, with responses grounded in fixed Grafana/PromQL queries for node, switch, and link metrics.

Wraps the Remnawave panel API into 22 callable tools so AI assistants can manage VPN nodes, users, squads, config profiles, and hosts through natural language instead of manual curl requests. It supports listing, creating, enabling, disabling, restarting, and extending entities, along with traffic resets and node key generation, using credentials supplied via environment variables.

Enables AI agents to inspect an OpenDaylight TransportPCE optical network — topology, port mappings, node status, services, TAPI views and advisory path computation — through a single RESTCONF-backed interface. Provisioning calls such as service create/delete and device connect are validated and queued for out-of-band human approval instead of being executed, and responses come back as structured JSON so failures are distinguishable from successes.

Enables AI agents to interact with Fortinet FortiManager through a minimal MCP interface using sandboxed JavaScript for querying the API spec and executing JSON-RPC calls.

Enables AI agents to make auditable, conditional edits to supported network inventory device fields through the community REST API, retaining durable history, receipts, and conflict-aware optimistic undo and reconciliation.