"How to open desktop applications on Windows" matching MCP servers:

MCP server that routes Claude Desktop chat into Claude Code, enabling headless execution and terminal handoff with session continuity.

Enables LLMs to capture desktop screenshots and control the mouse and keyboard on Linux, including Wayland, through MCP.

MCP server that enables AI tools to control local browser sessions for ChatGPT, Claude, and other AI services, supporting querying, navigation, file uploads, and artifact management.

Enables ChatGPT to control multiple registered Windows devices through a self-hosted gateway, routing Desktop Commander tool calls to specific workers by device ID.

Enables AI agents to capture multi-monitor screenshots with coordinate grids and perform mouse, keyboard, scrolling, dragging, and window-management actions on Windows via MCP tools or CLI. It provides pixel-accurate desktop automation for computer-use agents.

A lightweight server that enables AI agents to interact with the Windows operating system, allowing for file navigation, application control, UI interaction, and QA testing through various tools.

Enables multiple local AI desktop applications to exchange MCP messages and collaborate through a shared JSONL room file, with role-based routing, history, and audit session tools.

Routes every Claude Code/Hermes prompt through a local LLM planner and Open-Jev probe, injecting calibrated probability context while failing open if local services are unavailable.

Enables multiple MCP agents to read and write a single user-controlled, local-first fact layer under one user identity with explicit scopes, preserving sources, versions, permissions, and audit history. Supports structured memories such as preferences, facts, task state, and decisions, plus structured handoff capsules so one agent can resume another's work by task ID.

Enables running a stateless Model Context Protocol server over Streamable HTTP on Cloudflare Workers or any fetch-capable runtime, with signed sessions, origin checks, and JSON-RPC request handling. It lets developers define tools with JSON Schema validation and per-request context.

Enables Claude Code, Cursor, and Codex users to orchestrate plan/build/review workflows across host or CLI models with a spec gate, tool vetting, hard per-run and per-day cost/token limits, safe defaults, and clear logs.

Enables durable bidirectional handoffs between any MCP client and OpenAI Codex Desktop tasks, with persistent callbacks, acknowledgements, and session-scoped state across restarts.

Enables Claude to delegate web search, page reading, text drafting, and parallel multi-model image generation to cheaper helper models on any OpenAI-compatible backend. Claude stays in charge of planning and final decisions while consuming fewer of its own tokens.

Connects Claude Code and Codex to Jev-compatible System One services for context compaction, completion verification, and decision tasks like screening, classification, and gating.

Enables AI agents and IDEs to discover, install, and execute skills over Model Context Protocol via stdio or SSE, with semantic search and framework bridges.

Enables MCP clients to interact with A2A agents through four ordinary tools, translating agent discovery, messaging, task reading, and cancellation between the A2A and MCP protocols, with support for the tasks extension.

Acts as a bridge between standard REST/OpenAPI web APIs and the Model Context Protocol, dynamically converting REST endpoints into MCP tools for LLM clients like Cursor, Claude Desktop, and n8n.

An MCP server that turns a one-sentence idea into working, tested code using a pipeline of six AI agents, with optional deployment.

Enables MCP clients such as Claude Desktop to hand tasks to a running DeepSeek Harness window, where each task becomes a real session visible in the sidebar with a reusable session id. If the in-process plugin is unavailable, it falls back to running the task headless so the tool still returns a result.

Turns any OpenAPI/Swagger specification into a functional MCP server, dynamically exposing API endpoints as LLM tools or generating standalone Python code.