"Testing subscribe functionality on a Python server" matching MCP servers:

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

A production-grade MCP server providing a persistent Python REPL with multi-session support, sandboxing, and timeout protection, enabling LLM agents to execute Python code across multiple turns with variables that persist between calls.

Execute Python code via subprocess with timeout and error handling, returning stdout, stderr, and exit code.

A comprehensive MCP implementation designed for fullstack development that enables code manipulation, terminal command execution, and system notifications. It provides an intelligent agent interface powered by Gemini to automate Python and Next.js development workflows.

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.

Executes Python code with safety constraints and manages Python packages through the Model Context Protocol.

一个基于MCP的Python REPL服务器，支持多会话管理、代码执行、历史记录回放和包安装，为AI提供Python解释器能力。

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

Enables AI assistants to securely interact with IBM i (AS/400) systems via ODBC, supporting SQL queries, CL commands, source code reading, compilation, and spoolfile analysis.

Enables ChatGPT's web interface to operate a real Mac by executing shell commands and reading or writing files over a reverse SSH tunnel, without installing a client or consuming API quota.

A Python-based MCP server demonstrating basic math and text tools, supporting both SSE and STDIO transports for integration with AI assistants like Cline in VS Code.

Gives ChatGPT hands-on control of a local machine: reading, patching and executing code in approved project folders, running real interactive processes, managing plans and worker sub-chats, and driving the browser or desktop through user-granted permissions. Every capability is a switch inside an approved-folder sandbox, so nothing runs that the user did not explicitly enable.

Provides interactive Python REPL capabilities with persistent sessions, virtual environment support, package management via uv, and development tools like testing, linting, and code formatting for Python projects.

This is a secure Python code execution server that enables LLMs to run Python code safely in isolated Docker containers, supporting stdout capture and Matplotlib PNG generation.

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

Enables ChatGPT to work on a local project by reading and editing files, running shell commands, keeping terminals and desktop sessions open, and splitting work across durable workers whose context persists between tasks. Long-running work can be steered mid-flight, tracked with Goal, and carried into fresh chats via Compact & Resume.

Lets ChatGPT work directly on a local project by reading and editing files, running shell commands and tests, keeping terminals open, and using the user's desktop, all paired with an approved workspace folder. It also splits independent jobs across persistent workers that retain context, while riding the user's existing ChatGPT plan rather than Codex quota.

Enables executing Python code, managing environments and packages, and performing file operations within Docker containers.

A Python MCP server that lets MCP-compatible clients inspect and operate AWS through the AWS CLI, with command execution, suggestions, region lookup, and caller identity checks.

Enables AI assistants to manage remote servers via SSH with 14 commands for execution, file transfer, auditing, and monitoring.