"A GitHub server implementing the Model Context Protocol (MCP)" 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.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

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.

A Model Context Protocol (MCP) server that provides VSCode context and filesystem operations for AI assistants.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Provides 29 Git operations and 11 workflow combinations for AI assistants and developers, enabling comprehensive Git repository management through a standardized interface.

Wraps GitHub Copilot CLI as an MCP server, enabling MCP clients to run Copilot conversations for code tasks with support for session resumption and permission modes.

Provides AI coding assistants with context optimization tools including targeted file analysis, intelligent terminal command execution with LLM-powered output extraction, and web research capabilities. Helps reduce token usage by extracting only relevant information instead of processing entire files and command outputs.

Wraps the GitHub Copilot CLI to provide natural language command suggestions, explanations, and shell configuration for shell, git, and GitHub CLI commands through the Model Context Protocol.

A server that manages conversation context for LLM interactions, storing recent prompts and providing relevant context for each user via REST API endpoints.

Enables querying today's GitHub commits, performing local git operations (status, diff, add, commit, push), and creating GitHub issues through natural language.

Exposes persistent, stateful remote Bash sessions to AI agents via SSH, enabling command execution with preserved working directory and environment.

A distributable Model Context Protocol (MCP) server that exposes Dart SDK commands for AI-powered development. This server bridges the gap between AI coding assistants and Dart/Flutter development workflows by implementing the Model Context Protocol (MCP).

Read-only MCP server for TrueNAS Scale debugging, providing k3s tools for kubectl operations and whitelisted midclt calls for system info, apps, and pools.

Enables AI clients to operate on a remote Linux server over MCP, allowing shell command execution, file editing, package installation, project builds, and service management.

Automates Ansys Fluent simulation workflows, enabling environment checks, case execution, UDF management, and result export through MCP tools.

An MCP server that folds function and class implementations into structural skeletons while preserving signatures, interfaces, and docstrings, reducing tokens by up to 90%+ for AI agents. Exposes tools to get repository skeletons, unfold specific symbols on demand, and retrieve exact token and prompt cost savings metrics.

Exposes Creatio CLI (CLIO) commands as tools for AI agents to manage Creatio environments. It enables users to perform environment health checks, restart web applications, and execute raw CLI commands through a stateless HTTP transport.

An MCP front-end for AnB. The tool surface is "use-don't-reveal": no tool returns a plaintext secret. Reveal paths require a TTY the server doesn't have, so the no-reveal guarantee is structural, not prompt-based — it holds even against a prompt-injected agent. Runs as a dedicated, narrowly-scoped AnB identity; exec is default-deny (only allowlist rules tagged scope=mcp run); command output

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.