"Session" matching MCP servers:

Enables AI agents to establish and manage persistent SSH connections to remote hosts for executing commands. Supports SSH config files, multi-host management, and automatic reconnection with thread-safe concurrent operations.

SSH Session MCP fills a gap in the MCP ecosystem by offering a persistent shared SSH PTY runtime, not just stateless command execution. It features browser collaboration, input locking, safe/full execution modes, async command tracking, configurable policy rules, and multi-device profiles. Ideal for remote development, embedded systems, infrastructure workflows, and hardware control scenarios.

Lets an MCP client read output from and write commands to a single Termius terminal you explicitly share, with per-write and per-read approval inside the app.

Provides persistent interactive shell sessions via pseudo-terminals for MCP agents, enabling bidirectional communication, incremental reads, and stateful command execution across steps.

Enables AI agents to create and control persistent terminal sessions, run and monitor asynchronous jobs, page through ordered event history, and resolve registered device connection details without exposing stored secrets. Exposes 15 MCP tools over stdio that mirror a REST API, keeping session state alive independently of the agent that started it.

An MCP server that enables AI agents to establish and manage persistent SSH sessions with smart command execution, async support, and file operations.

Enables semantic search of shell session history, matching user intents to relevant CLI commands for keyboard-first developer workflows.

Enables semantic search of shell session history, matching natural-language intents to past CLI commands, including Warp sessions, for fast keyboard-first command discovery and reuse.

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

Enables code execution in isolated Docker containers with persistent IPython, Node.js, or R kernels, supporting file import/export and cross-session transfers via MCP tools.

A high-performance MCP server that manages persistent SSH sessions via a local tmux instance, enabling command execution, file transfer, and session monitoring for AI agents.

Local MCP server that exposes iTerm2 tab/session logs to MCP-capable agents via AppleScript, enabling tools to list open tabs and retrieve terminal scrollback.

A persistent, stateful MCP server that exposes a detached tmux session to clients, enabling shell command execution, terminal buffer reading, and control signal sending via JSON-RPC over stdio.

Lets Claude manage tmux sessions on Linux — start long-running ML training jobs, check their output, send keystrokes, and kill them.

Enables agents to launch and control interactive terminal sessions, inspecting screen text and formatting while sending keyboard and mouse input. Supports real pseudoterminals with resizing, snapshots, and session lifecycle management.

Lets an agent load a design once into a long-lived OpenSTA session and then run static timing and power analysis through dedicated tools or arbitrary Tcl commands. Enables setup/hold slack, TNS/WNS, fmax, DRV, and power queries against the live session.

agentic_ssh is written in Rust and specifically engineered to provide agent-hardened, token-efficient, and asynchronous SSH orchestrations for AI agents. It automatically discovers hosts from your local SSH configurations, manages connection heartbeats, handles silent network dropouts, and supports detached background job scheduling with isolated session logging

An MCP server for driving an ITS session on a PiDP-10 emulator over raw TCP, supporting persistent connections, raw control-byte transmission, and escape syntax for DDT commands. It enables interaction with ITS systems through natural language via MCP tools like open, send, read, and status.

Enables coding agents to control and inspect a running Herdr terminal session, including listing workspaces, tabs, panes, and agents, reading pane output, prompting agents, sending keys and commands, waiting for output or state, and splitting or closing panes.

Drive Elixir terminal UIs headlessly from an agent: start a TUI session, send keystrokes, take structured screenshots, and read TEA model state as MCP resources. Also exposes adaptive-UI recommendation tools and, when raxol_agent is loaded, read-only coding-agent session tools.