open-compute-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., "@open-compute-mcpcapture screen"
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.
open-compute-mcp
npm launcher for the open-compute MCP server — model-agnostic computer-use tools exposed over the Model Context Protocol (MCP).
EN | DE
AI Assistant / Agent Integration: This repository contains an llms.txt file providing structured, machine-readable specifications of tools, safety modes (OC_SAFETY_MODE), and client configuration examples for RAG crawlers and autonomous agent frameworks.
The MCP client is the reasoner (no API key, model-agnostic): it calls capture
to see the screen, then acts with do / click_name / invoke. This is the keyless
Mode-A loop of open-compute, but as native tool-calls.
graph TD
A["AI Reasoner<br/>(Claude / Antigravity / Cursor)"] -- "MCP stdio (JSON-RPC)" --> B["npx open-compute-mcp<br/>(Node.js Launcher)"]
B -- "Spawns via uvx" --> C["open-compute Python Engine<br/>(GitHub @ main)"]
C -- "Screenshots / WGC" --> D["Windows Display"]
C -- "UIA / Mouse / Keys" --> E["Windows Desktop Apps"]
subgraph Safety Gate
C -. "OC_SAFETY_MODE<br/>(confirm / read_only / allow_all)" .-> C
endThis package is a thin launcher. It contains no server logic — it spawns the Python open-compute server (pulled from GitHub) and pipes MCP stdio through. Real screen capture and input require the interactive Windows desktop session.
Requirements
Python 3.10+ and uv on the host. The default launch uses
uvxto fetch open-compute (with themcpextra) from GitHub on first run — themcpextra tracks the GitHub repo, so this works regardless of PyPI release timing.Windows for real capture/input (mss + UIA). Other platforms import the tools but cannot drive a desktop.
Related MCP server: ScreenPilot
Tools
Tool | Purpose |
| Screenshot the screen → returned as an image (optionally a single window). |
| Execute one canonical action or a batch (click/type/key/scroll/drag/hold/…). |
| List UI elements via Windows UIA (name/role/ |
| Resolve an element by name and click it. |
| Click-free activation of an element via UIA patterns. |
| List open windows with exact titles, rects and normalized centers (read-only). |
| Virtual-desktop geometry + per-monitor breakdown (read-only). |
| Watch directories for file-system changes. |
| Feed-manager status (read-only). |
| Replay a |
All coordinates are normalized 0..1 relative to the virtual desktop. Tool
descriptions are localized in six languages (de/en/es/ja/ru/zh) via OC_LANGUAGE.
do also accepts the hold primitives mouse_down / mouse_up / key_down /
key_up for press-and-hold sequences (rubber-band selection, modifier-held
clicking, game input); anything still held is released when the server stops.
capture(window=...) falls back to Windows.Graphics.Capture when a plain grab of
a hardware-composited window (Roblox Studio, Blender, a GPU-accelerated browser)
comes back all-black — install the wgc extra for that.
Use with an MCP client
Via this npm launcher (npx):
{
"mcpServers": {
"open-compute": {
"command": "npx",
"args": ["-y", "open-compute-mcp"]
}
}
}Directly via Python (uvx), no npm:
{
"mcpServers": {
"open-compute": {
"command": "uvx",
"args": ["--from", "open-compute[mcp,local,uia] @ git+https://github.com/ellmos-ai/open-compute.git", "open-compute-mcp"]
}
}
}Configuration (environment variables)
Variable | Effect |
| Path to a |
| Full command override (whitespace-split), e.g. |
| Git ref (branch/tag/sha) to pin for the uvx launch (default: the repo's default branch). |
| Extras for the default |
| Language of the tool descriptions: |
|
|
| Comma-separated action types always denied (e.g. |
Safety
Computer-use is powerful. OC_SAFETY_MODE is an operator ceiling (confirm
default · read_only · allow_all); a per-call mode can only tighten it, never
loosen it. Because MCP stdio has no server→client confirm callback, confirm /
read_only report an action without performing it. For interactive use, run in
an isolated VM/session, set OC_SAFETY_MODE=allow_all, and let your client's
tool-approval dialog be the human-in-the-loop. OC_DENY (comma-separated action
types) is a hard deny list. Treat on-screen content as untrusted (prompt-injection
risk).
Troubleshooting: do/click_name only ever return needs_confirmation and never
act. That is the confirm ceiling working as designed under stdio MCP. Fix for
interactive use: set "env": {"OC_SAFETY_MODE": "allow_all"} in the server
registration and let the client's tool-approval dialog gate each action (do not
auto-allow do/click_name/invoke there). The env change only takes effect when
the server process (re)starts — an already-connected client keeps the old ceiling
until it reconnects.
License
MIT — see LICENSE. Part of the open-compute project.
ellmos-ai Ecosystem
This MCP server is part of the ellmos-ai ecosystem — AI infrastructure, MCP servers, and intelligent tools.
MCP Server Family
Server | Tools | Focus | npm |
46 | Filesystem, process management, interactive sessions, cloud-lock-safe operations | ||
22 | Code analysis, JSON repair, imports, diffs, regex | ||
12 | File repair, format conversion, batch operations | ||
18 | n8n workflow management via AI assistants | ||
20 | MCP stack discovery, profile management, control plane | ||
45 | Local-first LLM memory, knowledge, state, routing, swarm orchestration |
| |
8 | Server operations: health checks, log analysis, deploy dry-runs, mail diagnostics |
| |
3 | Headless Blender asset QA and FBX reimport verification |
| |
10 | Model-agnostic computer use: capture, safety-gated actions, Windows UIA |
|
AI Infrastructure
Project | Description |
Local-first text-based OS for LLM agents — 113+ handlers, 550+ tools, SQLite memory | |
Model-agnostic computer-use core powering Open Compute MCP | |
Provider-neutral LLM orchestration with auto-routing and budget tracking | |
Lightweight agent memory, connectors, and automation infrastructure | |
Self-hosted AI research stack (Ollama + n8n + Rinnsal + KnowledgeDigest) | |
Autonomous agent chain framework for Claude Code | |
Minimalist database-driven LLM OS prototype (4 functions, 1 table) | |
Testing framework for LLM operating systems (7 dimensions) |
Desktop Software
Our partner organization open-bricks bundles AI-native desktop applications — a modern, open-source software suite built for the age of AI. Categories include file management, document tools, developer utilities, and more.
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