"IBM MCP Context Forge - Model Context Protocol Framework" matching MCP servers:

A lightweight service that enables AI assistants to execute AWS CLI commands through the Model Context Protocol (MCP), allowing AI tools to retrieve AWS documentation and interact with AWS services.

An MCP server for integrating AI models with client applications, allowing for structured interactions with APIs using command-line arguments for authentication and configuration.

A comprehensive production-ready MCP server with AI integration, plugin management, and web-based administration. Features multi-database support, RAG capabilities, SSH/SFTP access, and a built-in plugin hub for managing the MCP ecosystem.

Connects AI assistants to a Kali Linux terminal for executing security tools, managing interactive shell sessions, and performing penetration testing, CTF challenges, and security research tasks.

Gaia Protocol—a planetary DAO for global resource management using quantum-entangled ledgers and algorithmic governance.

Connects an MCP conversation to explicitly authorized user-owned machines over OpenSSH, enabling host discovery, operator-approved planning, command execution, and persistent receipts under controlled access.

A deliberately narrow, approval-gated workspace server that safely reads and writes files and runs allowlisted commands only inside one configured workspace, requiring visible approval for every write, process execution, and file read, with stale-overwrite protection and symlink-escape rejection.

A production-grade, type-safe MCP server for memory forensics via Volatility 3, enabling LLM-assisted incident response without timeouts or evidence spoliation.

This project implements a customizable MCP server to execute RTE protocol. The intention of this project is to be easily extensible. You can add your own MCP tools by using RteUtils class. Also is needed to define the RTE connection parameters and the RTE flow in a yaml format.

Enforces mandatory human approval before LLM agents can edit files, create files, or execute shell commands, using session tokens and audit logging.

Interactive, persistent terminal sessions for AI assistants via Model Context Protocol.

A Python framework that enables secure hardware control through the Model Context Protocol, allowing AI agents and automation systems to interact with physical devices across multiple platforms.

Enables AI agents to securely use real secrets (API keys, database passwords) by requiring human approval for each release, ensuring secrets never enter the model's context.

A TypeScript-based server that enables programmatic management of pseudo-terminal sessions. It allows users to spawn, control, and interact with terminal processes in real-time through the Model Context Protocol.

Enables management of BTRFS snapshots via Snapper and monitoring of BTRFS filesystem health through the Model Context Protocol.

SSH MCP is a Model Context Protocol tool for managing and interacting with multiple virtual machines over SSH. It simplifies executing commands on remote servers using the standard SSH config file format.

Provides comprehensive PC control capabilities including file operations (read, write, edit, delete), directory management, file search, and shell command execution through the Model Context Protocol.

An enhanced Model Context Protocol filesystem server that fixes common limitations and adds features like glob pattern search, head/tail reading, intelligent file editing with syntax validation, and new tools for delete and command execution.

A collection of Model Context Protocol servers that enable Claude Desktop to provide development assistance capabilities with filesystem, Git, shell command, and web search functionality without incurring API usage costs.

A secure shell command execution server implementing the Model Context Protocol (MCP). This server allows remote execution of whitelisted shell commands with support for stdin input.