sonu-davinceResolve-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@sonu-davinceResolve-mcpStart a task to open Notepad and type 'Hello MCP'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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
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.
Desktop Control & Shortcuts:
Complete keyboard control: write text, press specific keys, or dispatch multi-key hotkey combos (like
Ctrl + Alt + TorCtrl + 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.
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_taskreleases the lock, restoring the server to an idle state.
Related MCP server: desktop-touch-mcp
Architecture Flow
The operational flow of the server is represented in the diagram below:

(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.txt3. Environment Configuration
Copy .env.example to .env and fill in your API credentials:
cp .env.example .envUpdate 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 tohttp://localhost:11434.
Usage
Run the Server
The server runs over standard I/O (stdio). You can start it using python:
python -m src.serverOr install it as a package and use the console entry point:
pip install -e .
sonu-mcp-serverClient 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.pyMCP Tool Definition Registry
The following tools are exposed by this MCP server:
Tool Category | Tool Name | Parameters | Description |
Lifecycle |
|
| Start a task and lock the automation session. |
|
| Complete the active task and release the lock. | |
| None | Get current active task status. | |
| None | Reset and clear locks in case of error. | |
Automation |
|
| Mouse click at coordinates. Guarded. |
|
| Cursor move. Guarded. | |
|
| Mouse drag. Guarded. | |
|
| Scroll up/down. Guarded. | |
|
| Type string. Guarded. | |
|
| Press single keyboard button. Guarded. | |
|
| Press hotkey combo (e.g. | |
|
| Capture screen snapshot. Guarded. | |
LLM Router |
|
| Query a provider (ollama/openai/anthropic). |
| 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"
}
}
}
}This server cannot be installed
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