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Sonu DavinceResolve

БесплатноНе проверен

An MCP server that connects LLMs (Ollama, OpenAI, Anthropic) with desktop automation (mouse, keyboard, screenshots) using PyAutoGUI, with exclusive task locking

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Описание

An MCP server that connects LLMs (Ollama, OpenAI, Anthropic) with desktop automation (mouse, keyboard, screenshots) using PyAutoGUI, with exclusive task locking to prevent concurrent execution.

README


license: mit language:

  • en tags:
  • mcp
  • model-context-protocol
  • desktop-automation
  • llm
  • ollama
  • openai
  • anthropic
  • pyautogui
  • python pipeline_tag: text-generation library_name: mcp

sonu-davinceResolve-mcp

A Model Context Protocol (MCP) server that acts as a desktop automation assistant. It connects local or cloud LLMs (Ollama, OpenAI, Claude/Anthropic) with desktop automation capabilities (PyAutoGUI mouse, keyboard, shortcuts, screenshots) and implements an exclusive task lock to ensure tasks run to completion without interruption.

Features

  1. Multi-LLM Router:
    • Query local models run through Ollama (e.g. Llama 3, Mistral, Gemma).
    • Route query requests to OpenAI (GPT-4o, etc.) and Anthropic (Claude 3.5 Sonnet, etc.).
    • Unified interface for all local and cloud prompt routing.
  2. Desktop Control & Shortcuts:
    • Complete keyboard control: write text, press specific keys, or dispatch multi-key hotkey combos (like Ctrl + Alt + T or Ctrl + S).
    • Mouse control: clicks (left, right, middle), dragging, relative or absolute moves, and scroll wheel actions.
    • Screen capture utility to take snapshots and save to files.
  3. Exclusive Task Locking:
    • Prevent parallel task execution or concurrent client requests.
    • Once a task starts via start_task, an exclusive cross-process lock is acquired. All subsequent automation tools are guarded and verified against this lock.
    • Once complete, complete_task releases the lock, restoring the server to an idle state.

Architecture Flow

The operational flow of the server is represented in the diagram below:

MCP Flow Diagram

(For raw vector format, see docs/architecture.svg)


Setup & Installation

1. Prerequisites

  • Python >= 3.10
  • Ollama (Optional, for running free local models)

2. Install Dependencies

Initialize a virtual environment and install dependencies:

python -m venv venv
source venv/Scripts/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt

3. Environment Configuration

Copy .env.example to .env and fill in your API credentials:

cp .env.example .env

Update any API keys:

  • OPENAI_API_KEY: Required if routing to GPT models.
  • ANTHROPIC_API_KEY: Required if routing to Claude models.
  • OLLAMA_BASE_URL: Defaults to http://localhost:11434.

Usage

Run the Server

The server runs over standard I/O (stdio). You can start it using python:

python -m src.server

Or install it as a package and use the console entry point:

pip install -e .
sonu-mcp-server

Client Simulation Test

We provide a standalone test script to simulate client-side tool activation, task locking, mouse movement, key combos, and model list querying:

python examples/client_example.py

MCP Tool Definition Registry

The following tools are exposed by this MCP server:

Tool Category Tool Name Parameters Description
Lifecycle start_task task_id (str), description (str) Start a task and lock the automation session.
complete_task task_id (str), success (bool), details (str) Complete the active task and release the lock.
get_task_status None Get current active task status.
force_unlock None Reset and clear locks in case of error.
Automation click_mouse x (int), y (int), button (str), clicks (int) Mouse click at coordinates. Guarded.
move_mouse x (int), y (int), duration (float) Cursor move. Guarded.
drag_mouse x (int), y (int), duration (float), button (str) Mouse drag. Guarded.
scroll_mouse clicks (int) Scroll up/down. Guarded.
type_keyboard text (str), interval (float) Type string. Guarded.
press_key key (str) Press single keyboard button. Guarded.
press_hotkey keys (list[str]) Press hotkey combo (e.g. ['ctrl', 'c']). Guarded.
take_screenshot filename (str) Capture screen snapshot. Guarded.
LLM Router route_llm_query provider (str), model (str), prompt (str), system_prompt (str) Query a provider (ollama/openai/anthropic).
list_llm_models None List active provider models.

Integration with Claude Desktop

To integrate with Claude Desktop, add the server to your claude_desktop_config.json:

{
  "mcpServers": {
    "sonu-davinceResolve-mcp": {
      "command": "python",
      "args": ["-m", "src.server"],
      "cwd": "C:/Users/janmw/.gemini/antigravity-ide/scratch/sonu-davinceResolve-mcp",
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "ANTHROPIC_API_KEY": "your-anthropic-api-key"
      }
    }
  }
}

from github.com/S-onu112/sonu-davinceResolve-mcp

Установка Sonu DavinceResolve

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/S-onu112/sonu-davinceResolve-mcp

FAQ

Sonu DavinceResolve MCP бесплатный?

Да, Sonu DavinceResolve MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Sonu DavinceResolve?

Нет, Sonu DavinceResolve работает без API-ключей и переменных окружения.

Sonu DavinceResolve — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Sonu DavinceResolve в Claude Desktop, Claude Code или Cursor?

Открой Sonu DavinceResolve на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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