"Plotly Dash - A Python Framework for Building Interactive Web Dashboards" matching MCP servers:

interactive-mcp

A starter template for building Model Context Protocol (MCP) servers with mcp-framework. It includes an example tool and CLI for adding more tools.

MCP server that gives AI agents real interactive terminal sessions for running REPLs, SSH, database clients, and any interactive CLI with clean text output and smart completion detection.

A MCP server that enables human-in-the-loop workflow in AI-assisted development tools by allowing users to run commands, view their output, and provide textual feedback directly to the AI assistant.

MCP server for managing interactive processes, enabling AI agents to start, interact with, and terminate long-running programs like SSH sessions, REPLs, and installers via read/write operations.

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

Enables AI to present options and launch an interactive web or terminal interface for user selection, then return the results to the AI.

Enables LLMs to create and manage persistent, interactive shell sessions with full terminal emulation and PTY support. It allows for sequential command execution and supports interactive programs like vim or htop through specialized streaming and snapshot output modes.

MCP server that enables AI agents to run fully interactive SSH sessions (via tmux) and execute commands like a human operator, with persistent sessions and multiple concurrent connections.

Provides AI agents with fully interactive terminal sessions, including TUI support, keyboard control, and screen capture across Windows, Linux, and Mac.

Provides stateful, interactive terminal access for LLMs to spawn and maintain persistent processes like SSH sessions, debuggers, and REPLs with continuous input/output interaction across commands.

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.

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 ChatGPT web to use local tools like file reading, command execution, and patch application through an MCP server over OpenAI Secure MCP Tunnel.

MCP server that provides AI access to a local terminal, enabling command execution, directory navigation, and system operations with persistent session state.

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.

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.