"Learning to Create an Expert Python Program to Exit GitHub" matching MCP servers:

Enables AI agents to securely connect to and manage remote servers via SSH, with tools for running commands, file operations, log inspection, service management, and system monitoring under configurable access controls and audit logging.

A server that provides a persistent Python REPL environment through the MCP protocol, allowing execution of Python code, variable management, and package installation.

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.

A local MCP runtime for macOS and Windows that enables ChatGPT to read, edit, search, run tests, and capture screenshots in your local project folder while keeping your source code on your machine.

A Python server that enables interaction with macOS native applications (Contacts, Notes, Mail, Messages, Reminders, Calendar, and Maps) through AppleScript, featuring asynchronous operations and type-safe interfaces.

Enterprise-grade MCP server integrating Claude AI capabilities, enabling AI-powered conversations, file operations, and system tools via the Model Context Protocol.

A simple MCP server that exposes a terminal tool, allowing AI agents to execute shell commands.

The m2m-mcp-server-ssh-client provides a unified MCP server interface, securely connecting via SSH to the m2m-mcp-server-ssh-server back-end which aggregates MCP servers. This setup offers secure, single-point access to diverse remote tools using robust SSH key-based authentication.

An MCP server that enables AI assistants to execute shell commands and manage files on remote servers via SSH. It supports recursive directory uploads, archive extraction, and direct file creation from text content.

A Python implementation of the Model Context Protocol that allows applications to provide standardized context for LLMs, enabling creation of servers that expose data and functionality to LLM applications through resources, tools, and prompts.

A tutorial MCP server for learning the Model Context Protocol by building file and system tools. Provides hands-on experience creating custom tools that enable AI models to interact with files and execute system commands.

Enables AI assistants to execute Python functions and system commands via Streamable HTTP, including bash, Python code execution, file operations, and text searching.

Extends Claude Desktop with custom tools for file management, system operations, and command execution. Supports creating/reading/deleting files, directory listing, system information retrieval, and file searching capabilities.

A security-first MCP server that provides LLMs with structured tools for filesystem, process, search, build/test/lint, IDE integration, and more.

A simple Machine Conversational Protocol server for Warp Terminal that provides a basic greeting tool and personalized greeting resource.

Enables ChatGPT to securely operate a single Windows development workspace via a local MCP server, offering file editing, Git status, static analysis, approved test/build, and limited ADB operations with audit logging.

Enables remote log searching, tailing, and file reading across servers via MCP tools, with pluggable execution via SSH, pyinfra, or local commands.

Bridges Llama models with Claude Desktop through Ollama, enabling privacy-first local AI operations with 10+ built-in tools for file operations, web search, calculations, and custom model deployment. Features streaming support, hybrid intelligence workflows, and extensive Python ecosystem integration for research, development, and enterprise applications.

PRIMS is a lightweight, open-source Model Context Protocol (MCP) server that lets LLM agents safely execute arbitrary Python code in a secure, throw-away sandbox.

Provides safe, read-only access to memory analysis and debugging functionality through the Model Context Protocol, allowing users to examine computer memory for software development, security research, and educational purposes.