Connect any AI model to 1200+ integrations (MCP, CLI, API)

Model Context Protocol (MCP) server for pfSense firewall management. Control firewall rules, VPNs, DNS, DHCP and diagnostics in natural language from Claude Desktop, Claude Code or any MCP client — 333 wire-format-verified tools for the pfSense REST API, with safety guardrails, config backup and rollback on every change.

Desktop app that automatically scans and blocks malicious MCP traffic in AI apps like Cursor, Claude, VS Code and Windsurf.

pentestMCP: AI-Powered Penetration Testing via MCP, an MCP designed for penetration testers.

An MCP server for querying Solana transactions using natural language with Solscan API

A collection of servers which are deliberately vulnerable to learn Pentesting MCP Servers.

A Model Context Protocol server that connects AI assistants like Claude to AWS security services, allowing them to autonomously query, inspect, and analyze AWS infrastructure for security issues and misconfigurations.

Open-source governed, local-first memory control plane for AI agents and teams. arXiv:2608.08253

Tamper-evident integrity monitor for the MCP config & server files your local AI agents load.

A blazing fast AI Gateway with integrated guardrails. Route to 1,600+ LLMs, 50+ AI Guardrails with 1 fast & friendly API.

A plugin-based gateway that orchestrates other MCPs and allows developers to build upon it enterprise-grade agents.

Testing and evaluation platform to chat, inspect, and debug MCP servers, MCP apps, and ChatGPT apps.

ToolHive is an application that allows you to install, manage and run MCP servers and connect them to AI agents

Safe local execution layer for AI agent tools. Build, validate, and publish MCP tools with a no-pass-no-run workflow — cross-platform desktop app powered by Spring AI.

Connect Cursor, Copilot & Claude AI directly to Cheat Engine via MCP. Automate reverse engineering, pointer scanning, and memory analysis using natural language.

This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.