"APM Terminals" matching MCP servers:

Controls local purplemux (tmux + LLM workspace manager) from Claude Code/Codex, enabling cross-LLM orchestration by managing workspaces, tabs, terminals, and Electron browser via 16 tools.

MCP server that lets AI agents control Perssona. It enables creating terminals, managing canvas nodes, sending prompts, and running multi-agent workflows.

An MCP server that enables LLM agents to control a two-joint MuJoCo robot arm through tools for moving, reading state, and resetting. It deliberately omits inverse kinematics, so the agent must infer joint angles from observations.

Enables AI agents to see and control an existing Linux X11 desktop over SSH by taking screenshots and performing mouse, scroll, typing, and keyboard-shortcut actions across browsers, terminals, file managers, and other apps.

Provides a fail-closed MCP bridge to QMT trading terminals, enabling observe-only, simulated, manual live, and limited automatic trading with hard risk controls, two-phase trade intents, and strict authorization checks.

Enables AI agents to access real-time market data, manage Moomoo trading accounts, and execute trades via the Moomoo platform.

ht-mcp is useful for enabling Agents to use terminals (e.g. bash, zsh, fish) in the same way a human does. It solves the challenge of agents stalling when they encounter interactive terminal commands.

Enables MCP hosts to run a user-configurable agent with multi-engine orchestration, declarative connectors to third-party APIs, task-graph execution, audit ledger, and memory, without needing to clone or configure multiple repositories.

It gives AI agents one tool to access the Omega-API judge, which evaluates conversational turns and returns a decision and gate action (release, clarify, suppress, or none) to guide the agent's response.

AI-powered financial intelligence for autonomous trading agents. 9 MCP tools for real-time trading signals, risk index, market regime detection, stock analysis, commodity scoring, sector radar, and geopolitical intelligence briefings.

An orchestrator MCP server that takes a plain-language app description and guides agents through a full workflow from intake to deployment, including design, audit, and maintenance.

Monitoring that agents set up for themselves — cron jobs, CI/CD pipelines and AI agent runs.

Enables a supervisor agent to create, coordinate, steer, inspect, and interrupt multiple Codex agents as a subagent pool within an MCP host, running them alongside the host's own subagents.

The best free social media publishing and scheduling API. Publish to 11 platforms from a single API call. Schedule posts, upload media, track analytics, and automate your social media workflow.

This MCP server enables remote control and management of Claude Code agents, allowing you to execute missions, configure agent personalities, and integrate with other MCP tools.

Bridges MCP clients such as Claude Code and Cursor to independent Codex app-server sessions, letting them start, poll, steer, review, compact, cancel, and answer prompts for asynchronous Codex tasks over local stdio or a remote authenticated WebSocket. Runs read-only by default, with workspace-write sandboxing only when a user explicitly enables it, and reports job status, model listing, and progress back to the client.

Enables MCP clients to start new Codex conversations and continue existing threads, exposing codex and codex-reply tools over stdio via the Codex app-server protocol.

Provides persistent memory capabilities for AI assistants, enabling storage, recall, and analysis of information across conversations with intelligent memory management.

This server facilitates structured problem-solving by breaking down complex issues into sequential steps, supporting revisions, and enabling multiple solution paths through full MCP integration.

Manage and monitor Hadoop clusters via Apache Ambari API, enabling service operations, configuration changes, status checks, and request tracking through a unified MCP interface for simplified administration. * Guide: https://call518.medium.com/llm-based-ambari-control-via-mcp-8668a2b5ffb9