"An MCP server for Macaroon Network on glama.ai" matching MCP servers:

Provides MCP tools for governed multi-vendor network device operations, including configuration management (backup, diff, merge, replace, rollback) and read-only queries (facts, interfaces, BGP, LLDP, ARP) via NAPALM, with optional NetBox source-of-truth integration.

Open end-to-end encrypted messaging protocol and MCP server (a4a-mcp) that gives AI agents a cryptographic address (apub1...) to exchange messages, tasks, and signed agreements directly across NAT without port forwarding.

Provides an MCP server that tracks open loops (pending decisions or replies) across email, agent sessions, and other channels, enabling agents to query what is waiting on whom.

Enables read-only access to managed network devices over SSH or Telnet via MCP, allowing users to probe devices, retrieve redacted running or startup configs, gather facts and interfaces, back up multiple devices, and compare configs for drift or unsaved changes.

Enables AI assistants to understand lab topologies, follow operational principles, and interact with real network devices through observable terminals while keeping private access information hidden.

Local-first MCP server that lets AI agents design Cisco-style networks and generate L1/L2/L3 topology diagrams, device tables, and AI-ready context files.

A Model Context Protocol server providing network diagnostic tools for AI agents, including connectivity testing, batch operations, local network info, and pcap analysis.

Enables an AI assistant to search, inspect and run vendor API operations for HPE Aruba Networking Central, Juniper Mist and HPE Aruba Networking ClearPass through four tools covering tool discovery, read-only execution, full invocation with change classification, and per-product login checks. Writes and disruptive actions are refused or flagged, so network changes only happen with explicit approval.

MCP server enabling local network interaction, shell command execution, system resource monitoring, and SSH-based remote device management.

Enables AI agents to open persistent interactive terminal sessions with network devices over SSH, Telnet, TCP console, or serial, write raw commands including nested ssh/telnet transitions, and read full output without requiring a particular prompt format. It supports multiple concurrent sessions and keeps credentials/secrets out of MCP arguments or audit logs.

Enables agents to check a public hostname's declared agent policy, official API or developer path, provider status, and recent observations, returning a recommended action for blocked web steps.

Enables Claude Code to interact with network devices over serial and SSH with command safety classification and a persistent knowledge base.

Enables AI agents and MCP clients to connect to a live Esri ArcGIS Utility Network through the UtilityNetworkServer REST API, supporting trace, subnetwork, dirty-area, and association operations.

A social network MCP server that lets AI-powered IDEs connect and interact with other developers through messaging, public feed posts, resource sharing, and user discovery by tech stack.

An MCP server that connects AI assistants to YNAB budgets, enabling natural language queries about finances backed by full API coverage and built-in YNAB methodology knowledge.

Enables AI assistants to troubleshoot AWS and hybrid network connectivity by analyzing hop-by-hop paths across security groups, NACLs, route tables, Transit Gateway routes, VPN/BGP, DNS, and flow logs to identify blocking rules and suggest fixes.

Enables LLM agents to triage network incidents by fetching device telemetry, inspecting syslogs, and executing traffic reroutes through MCP tools.

Enables network discovery, port scanning, and infrastructure monitoring with device detection, service fingerprinting, and cluster health checks for autonomous AI systems.

MCP server for network operations that lets AI assistants interact with Cisco/Juniper network devices through safe, well-defined tools like compliance audits and configuration backups.

Enables querying UniFi Network sites, devices, and clients, retrieving device statistics, and restarting devices through the Model Context Protocol.

Aggregates network operations tools such as retrieving local network configurations and scanning ports, enabling IT professionals to perform these tasks via natural language.

Turns your UniFi Network Controller into programmable tools for querying and modifying network settings via MCP.

MCP server for Topaz switches: searches documentation, performs network diagnostics (ping, traceroute, port scanning, etc.), calculates subnets, and generates VLAN/base configurations. Also includes a web UI for use without an MCP client.

Enables AI agents to interact with Cisco IOS-XE network devices over SSH using structured tools. Provides read and write capabilities for network management with built-in validation and security.

Lets an LLM client monitor devices, services, disk usage, and uptime in a home network and home lab.

A secure MCP server for network diagnostics, providing tools like ping, traceroute, whois, nslookup, dig, nmap, curl, and netstat through natural language interfaces.

Enables MCP-capable AI clients to inspect live lab topology, manage terminal sessions, run commands, collect evidence, and support network investigation, troubleshooting, and validation while engineers retain control over managed definitions and decisions.

Provides real-time access to Pyth Network's decentralized oracle price feeds across 1,930+ assets and 107+ blockchains, enabling AI agents to fetch current prices, historical data, and TWAP calculations for crypto, equity, FX, metal, and rates markets.

Enables AI agents to debug and repair historical Solaris/SPARC systems by providing an out-of-band control plane with guest DTrace, QEMU monitor access, SPARC-aware GDB, host eBPF/perf tracing, and an immutable evidence ledger for cross-layer hypothesis testing.

An MCP server exposing every documented Email on Acid API v5 request as a tool — 24 tools across authentication, email client lists, email rendering testing, and spam testing.

IP Network AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables Alexa+ and other MCP clients to query live telemetry, including network status, measured energy consumption, and per-node GPU metrics, via Streamable HTTP.

A minimal MCP server with get_weather and create_ticket tools, used for testing MCP servers across protocol, unit, eval, transport, and auth layers.

Enables assistants to publish readable replies and status updates to e-ink displays and Home Assistant, with switchable characters and state retrieval through MCP tools.

Exposes the UniFi Network Integration API as MCP tools, dynamically loaded from JSON manifests, with read-only mode by default.

Enables AI agents to analyze PCAP files for network forensics using Wireshark/tshark, providing high-performance packet inspection, filtering, and protocol analysis through the Model Context Protocol.

Enables automated review and analysis of network security controls (AWS Security Groups, Network ACLs) using natural language queries. Supports NSC configuration reviews, network segmentation testing, and identifying security gaps through conversational LLM interaction.

Enables AI agents to safely troubleshoot networks through read-only tools for device inventory, interface status, VLAN paths, BGP neighbors, route lookups, and interface error detection. Integrates with Microsoft Copilot Studio and Teams for natural-language-driven network diagnostics.

A comprehensive Model Context Protocol (MCP) server implementing the latest MCP specification with tools, resources, prompts, and enhanced sampling capabilities that features HackerNews and GitHub API integrations for AI-powered analysis.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.