Open Computer Use

MCP server that gives any LLM its own computer — managed Docker workspaces with live browser, terminal, code execution, document skills, and autonomous sub-agents. Self-hosted, open-source, pluggable into any model.

Online demo: chat.yambr.com — Open WebUI with Computer Use already set up, sign in with GitHub or Google. (More ways to try it below.)

See it in action: Demo course on docs.yambr.com — eight live scenarios captured from the chat above (pitch deck, Word doc, Excel, PDF invoice, data chart, live-rendered landing page, web scrape, building a custom skill). Real prompts, real screenshots, copy-pasteable.

If any of this looks useful, a ⭐ on the repo really helps — thanks!

What is this?

An MCP server that gives any LLM a fully-equipped Ubuntu sandbox with isolated Docker containers. Think of it as your AI's computer — it can do everything a developer can do:

• Execute code — bash, Python, Node.js, Java in isolated containers
• Create documents — Word, Excel, PowerPoint, PDF with professional styling via skills
• Browse the web — Playwright + live CDP browser streaming (you see what AI sees in real-time)
• Run Claude Code — autonomous sub-agent with interactive terminal, MCP servers auto-configured
• Use 13+ skills — battle-tested workflows for document creation, web testing, design, and more

Built for production multi-user deployments. Tested with 1,000+ MAU. Each chat session runs in its own isolated Docker container — the AI can install packages, create files, run servers, and nothing leaks between users. Works seamlessly across MCP clients: start with Open WebUI today, switch to Claude Desktop or n8n tomorrow — same backend, no migration.

Key differentiators

Works with any MCP-compatible client: Open WebUI, Claude Desktop, LiteLLM, n8n, or your own integration. See docs/COMPARISON.md for a detailed comparison with alternatives.

Live browser streaming

File preview with skills

Frontend design — landing page rendered live in the browser tab

Presentations — custom design system, not the default white template

Build your own skills — package recurring work into reusable functions

Data → chart with analysis

Claude Code — interactive terminal in the cloud

Sub-agent dashboard — monitor and control

For all eight live scenarios with prompts you can copy-paste, see the Demo course. See docs/FEATURES.md for architecture details and docs/SCREENSHOTS.md for all screenshots.

Pro tip: Create skills with Claude Code in the terminal, then use them with any model in the chat. Skills are model-agnostic — write once, use everywhere.

Multi-CLI sub-agent runtime (v0.9.2.1+): The sub-agent dispatch supports Claude Code (default), OpenAI Codex, and OpenCode (with OpenRouter / qwen / DeepSeek / 75+ providers). Flip SUBAGENT_CLI=claude|codex|opencode in .env — see docs/multi-cli.md for the worked OpenCode + qwen3-coder + OpenRouter recipe.

Architecture

Looking ahead: a Kubernetes-friendly architecture with object-storage-backed user data and squashfs-packaged skills is being designed in docs/future-architecture/. Docker Compose remains the primary supported path.

Ways to try it

OAuth only — no email/password, no SMS. On chat.yambr.com models are bundled as a free convenience; the hosted API is tools-only. Canonical cloud docs: docs.yambr.com. Repo-side orientation: docs/CLOUD.md.

Quick Start

git clone https://github.com/Wide-Moat/open-computer-use.git
cd open-computer-use
cp .env.example .env
# Edit .env — set OPENAI_API_KEY (or any OpenAI-compatible provider)

# 1. Start Computer Use Server (builds workspace image on first run, ~15 min)
docker compose up --build

# 2. Start Open WebUI (in another terminal)
docker compose -f docker-compose.webui.yml up --build

Open http://localhost:3000 — Open WebUI with Computer Use ready to go.

Note: Two separate docker-compose files: docker-compose.yml (Computer Use Server) and docker-compose.webui.yml (Open WebUI). They communicate via localhost:8081. This mirrors real deployments where the server and UI run on different hosts.

Model Settings (important!)

After adding a model in Open WebUI, go to Model Settings and set:

Without Function Calling: Native, the model won't invoke Computer Use tools.

What's Inside the Sandbox

Skills

13 built-in public skills + 14 examples:

14 example skills: web-artifacts-builder, copy-editing, social-content, canvas-design, algorithmic-art, theme-factory, mcp-builder, and more.

See docs/SKILLS.md for details.

MCP Integration

The server speaks standard MCP over Streamable HTTP. Point any MCP client at it — hosted or self-hosted.

• Hosted: https://api.yambr.com/mcp/computer_use with Authorization: Bearer <key from app.yambr.com>. Client configs and full reference live on docs.yambr.com.
• Self-hosted: http://localhost:8081/mcp. Quick sanity check:
  bash

  curl -X POST http://localhost:8081/mcp \
    -H "Content-Type: application/json" \
    -H "X-Chat-Id: test" \
    -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2024-11-05","capabilities":{},"clientInfo":{"name":"test","version":"1.0"}}}'
  

  Full self-host integration guide (LiteLLM, Claude Desktop, custom clients): docs/MCP.md. The per-chat system prompt rides six redundant MCP-native channels (tool descriptions, /home/assistant/README.md in the sandbox, InitializeResult.instructions, resources/list for uploaded files, plus an HTTP /system-prompt endpoint for legacy integrations) — full map in docs/system-prompt.md.

Configuration

All settings via .env:

Custom Skills & Token Management (optional)

By default, all 13 built-in skills are available to everyone. For per-user skill access and custom skills, deploy the Settings Wrapper — see settings-wrapper/README.md.

Personal Access Tokens (PATs): The settings wrapper can also store encrypted per-user PATs for external services (GitLab, Confluence, Jira, etc.). The server fetches them by user email and injects into the sandbox — so each user's AI has access to their repos/docs without sharing credentials. The server-side code for token injection is implemented (docker_manager.py), but the Open WebUI tool doesn't pass the required headers yet. This is on the roadmap — if you need PAT management, open an issue.

MCP Client Integrations

The Computer Use Server speaks standard MCP over Streamable HTTP — any MCP-compatible client can connect. Open WebUI is the primary tested frontend, but not the only option.

Open WebUI Integration

Open WebUI is an extensible, self-hosted AI interface. We use it as the primary frontend because it supports tool calling, function filters, and artifacts — everything needed for Computer Use.

Compatibility: This build is strictly built and verified against Open WebUI 0.9.2. The first 3 segments of our build version (v0.9.2.X) always match the Open WebUI base version it targets. If you run a different Open WebUI version, pick the Open Computer Use build whose first 3 version segments match yours — e.g., for Open WebUI 0.8.12 use a v0.8.12.Y build.

Why not a fork? We intentionally did not fork Open WebUI. Instead, everything is bolted on via the official plugin API (tools + functions) and build-time patches for missing features. This means you can use stock Open WebUI 0.9.2 with this build (the version that the first 3 segments of our build version v0.9.2.X match) — just install the tool and filter. Patches are applied at Docker build time; strongly recommended — 4 of them affect user-visible UX (artifacts panel, preview iframe, error banners, large tool-result handling). Pulling ghcr.io/open-webui/open-webui directly skips all of them — see Required setup when embedding Open WebUI for the full checklist.

Running Claude Code through a corporate gateway (LiteLLM, Azure, Bedrock)? See docs/claude-code-gateway.md for the three-path operator recipe.

The openwebui/ directory contains:

• tools/ — MCP client tool (thin proxy to Computer Use Server). Required — this is the bridge between Open WebUI and the sandbox.
• functions/ — System prompt injector + file link rewriter + archive button. Required — without it the model doesn't know about skills and file URLs.
• patches/ — Build-time fixes for artifacts, error handling, file preview. Optional but recommended — improves UX significantly.
• init.sh — Auto-installs tool + filter on first startup. Optional — you can install manually via Workspace UI instead.
• Dockerfile — Builds a patched Open WebUI image with auto-init. Optional — use stock Open WebUI + manual setup if you prefer.

How auto-init works

On first docker compose up, the init script automatically:

1. Creates an admin user (admin@open-computer-use.dev / admin)
2. Installs the Computer Use tool via POST /api/v1/tools/create
3. Installs the Computer Use filter via POST /api/v1/functions/create
4. Configures tool and filter valves (ORCHESTRATOR_URL=http://computer-use-server:8081 — internal URL for server↔server, seeded into both Valves)
5. Marks the tool public-read (access grants for both group:* and user:* wildcards) — so non-admin users see the tool in their workspace
6. Marks the filter both active and global (two separate toggles: /toggle and /toggle/global) — active-but-not-global is silently inert and a common manual-setup mistake
7. Merges {function_calling: "native", stream_response: true} into DEFAULT_MODEL_PARAMS via POST /api/v1/configs/models — every model gets the right defaults without per-model Advanced Params clicks

A marker file (.computer-use-initialized) prevents re-running on subsequent starts.

Note: Open WebUI doesn't support pre-installed tools from the filesystem — they must be loaded via the REST API. The init script automates this so you don't have to do it manually.

Manual setup (if not using docker-compose)

If you run Open WebUI separately, you need to manually:

1. Go to Workspace > Tools → Create new tool → paste contents of openwebui/tools/computer_use_tools.py
2. Set Tool ID to ai_computer_use (required for filter to work)
3. Configure Valves: ORCHESTRATOR_URL = internal URL of your Computer Use Server (http://computer-use-server:8081 for Docker compose)
4. Open the tool's ⋯ → Share menu and set access to Public (grants read to both group:* and user:* wildcards) — otherwise only your admin account sees the tool and non-admin users get an empty tool list with no error
5. Go to Workspace > Functions → Create new function → paste openwebui/functions/computer_link_filter.py
6. Enable the filter: toggle Active and toggle Global in the Functions list — these are two separate switches, and active-but-not-global means the filter loads but is never applied to chats
7. In your model settings, set Function Calling = Native and Stream Chat Response = On. Or set them globally once in Admin → Settings → Models → Advanced Params (function_calling: native, stream_response: true) — that becomes DEFAULT_MODEL_PARAMS for every model.

The docker-compose stack handles all of this automatically.

Required setup when embedding Open WebUI into your own stack

If you run Open WebUI outside the stock docker-compose.webui.yml — your own compose, Kubernetes, Portainer, or a downstream repo — there are four traps that will silently break Computer Use. All four hit us in production. Check in this order.

Step 1 — Build the image from openwebui/Dockerfile, don't pull upstream

Pulling ghcr.io/open-webui/open-webui:vX.Y.Z gives you a stock image without any of this repo's patches. Four of them are critical for UX:

Only CHAT_RESPONSE_MAX_TOOL_CALL_RETRIES keeps working on an upstream image (it's a stock Open WebUI env) — which creates a false "everything is configured" feeling.

Use build: in your downstream compose, mirroring docker-compose.webui.yml:11-15:

services:
  open-webui:
    build:
      context: ./openwebui   # path into this repo
      dockerfile: Dockerfile
      args:
        OPENWEBUI_VERSION: "0.9.2"
    image: open-webui-with-cu-patches:latest   # local tag, do not pull

Verify the patches are baked into the running container:

docker exec open-webui bash -c \
  'grep -rl "FIX_ARTIFACTS_AUTO_SHOW" /app/build/_app/immutable/chunks/ >/dev/null \
   && echo "patches applied" || echo "MISSING — you are on upstream image"'

The FIX_ARTIFACTS_AUTO_SHOW JS comment marker is injected by fix_artifacts_auto_show.py at build time as a version-stable identifier — it does not depend on minified Svelte variable names, which change with every Open WebUI release.

Step 2 — No build-arg required for preview URL detection (host-agnostic since v0.9.2.0)

fix_preview_url_detection is now fully host-agnostic. The injected JS reads the origin directly from the matched URL at runtime (_pm[1] captures the full https://host:port prefix), so the patch requires no build-time host configuration. The COMPUTER_USE_SERVER_URL build-arg has been removed from openwebui/Dockerfile.

No action needed — the patch works automatically regardless of whether you use localhost:8081, a public domain, or Docker internal DNS. The preview iframe src is always reconstructed from the URL the model wrote into the message, which in turn comes from the server's PUBLIC_BASE_URL env var.

Verify the patch is applied:

docker exec open-webui bash -c \
  'grep -rl "FIX_PREVIEW_URL_DETECTION" /app/build/_app/immutable/chunks/ >/dev/null \
   && echo "patches applied" || echo "MISSING — fix_preview_url_detection not baked in"'
# → should print "patches applied"

Step 3 — Two URL settings, two roles (public vs internal)

v4.0.0: the old "three FILE_SERVER_URL places that must match" footgun is gone. There are now only two places and two distinct roles — public (browser-reachable) vs internal (Docker-local). The COMPUTER_USE_SERVER_URL build-arg was removed in v0.9.2.0 — fix_preview_url_detection is now host-agnostic (see Step 2).

⚠️ Do NOT point ORCHESTRATOR_URL at your public domain. It technically works, but every MCP request then goes browser→CDN→Traefik→container. Any hiccup in that chain kills the stream mid-tool-call and the user sees MCP call failed: Session terminated. Stay inside the Docker network.

The filter no longer has a public-URL Valve at all — it reads the public URL from the server's X-Public-Base-URL response header and caches it alongside the prompt. One public knob, one internal knob.

See also docs/openwebui-filter.md.

Step 4 — Four env vars on the open-webui container

Copy-paste into your downstream compose environment: block:

services:
  open-webui:
    environment:
      # --- Computer Use required env vars (read by build-time patches) ---
      - CHAT_RESPONSE_MAX_TOOL_CALL_RETRIES=200
      - TOOL_RESULT_MAX_CHARS=50000
      - TOOL_RESULT_PREVIEW_CHARS=2000
      # Internal URL of the Computer Use server — seeded by init.sh into both
      # Tool and Filter Valves, and read by the fix_large_tool_results patch.
      # Same Docker network: use the service DNS name.
      - ORCHESTRATOR_URL=http://computer-use-server:8081

Note: the last three are no-ops if the image is upstream ghcr.io — they need fix_large_tool_results from Step 1.

Step 5 — Filter must be global, tool must be public-read

Open WebUI has two separate switches for each function (is_active and is_global) and two required grants for each tool (group:* + user:*). The stock init.sh does this for you; manual / custom deployments commonly miss one side and then spend hours wondering why "everything is installed but nothing works."

Verify against the database (Postgres used by the stock stack; see docker-compose.webui.yml:53):

# Filter flags — expect (t, t):
docker exec <postgres-container> psql -U openwebui -d openwebui -c \
  "SELECT is_active, is_global FROM function WHERE id='computer_use_filter';"

# Tool grants — expect TWO rows (group|* and user|*, both 'read'):
docker exec <postgres-container> psql -U openwebui -d openwebui -c \
  "SELECT principal_type, principal_id, permission FROM access_grant WHERE resource_id='ai_computer_use';"

For SQLite-backed Open WebUI deployments, swap psql for sqlite3 /app/backend/data/webui.db with the same SQL.

Step 6 — Verify everything at once

# 1. Image has patches (marker-based — version-stable across Open WebUI releases):
docker exec open-webui bash -c \
  'grep -rl "FIX_ARTIFACTS_AUTO_SHOW" /app/build/_app/immutable/chunks/ >/dev/null \
   && echo OK || echo MISSING'

# 2. Preview URL detection is host-agnostic (no build-arg needed since v0.9.2.0):
docker exec open-webui bash -c \
  'grep -rl "FIX_PREVIEW_URL_DETECTION" /app/build/_app/immutable/chunks/ >/dev/null \
   && echo "patches applied" || echo "MISSING — fix_preview_url_detection not baked in"'
# → should print "patches applied"

# 3. Env vars reached the container:
docker exec open-webui env | grep -E 'CHAT_RESPONSE_MAX_TOOL_CALL_RETRIES|TOOL_RESULT_|ORCHESTRATOR_URL'

# 4. Tool+Filter Valve (Session-terminated trap) — Admin UI is simplest:
#    Workspace → Tools → ai_computer_use → Valves → ORCHESTRATOR_URL
#    Admin → Functions → computer_link_filter → Valves → ORCHESTRATOR_URL
#    → both must be http://computer-use-server:8081 (internal URL, Docker service DNS),
#      NOT your public domain.

# 5. Server env (baked into system prompt AND returned to filter via header):
docker exec computer-use-server env | grep ^PUBLIC_BASE_URL=
# → must be a URL your browser can reach (e.g. http://localhost:8081 for local dev).

# 7. Filter is ACTIVE *and* GLOBAL (see Step 5):
docker exec <postgres-container> psql -U openwebui -d openwebui -c \
  "SELECT is_active, is_global FROM function WHERE id='computer_use_filter';"
# → expect (t, t). Two 't's, not one.

# 8. Tool is public-read with both wildcards (see Step 5):
docker exec <postgres-container> psql -U openwebui -d openwebui -c \
  "SELECT principal_type, principal_id, permission FROM access_grant WHERE resource_id='ai_computer_use';"
# → expect TWO rows: (group, *, read) and (user, *, read).

After rebuilding the image, do a hard reload in the browser (Cmd+Shift+R / Ctrl+Shift+R). Otherwise it keeps the old cached JS chunks and you'll think the fix didn't work.

Symptom → which step is wrong

Security Notes

Production tested with 1000+ users on Open WebUI in a self-hosted environment. For public-facing deployments, see the hardening roadmap below.

Current model

• Docker socket: The server needs Docker socket access to manage sandbox containers. This grants significant host access — run in a trusted environment only.
• MCP_API_KEY: Set a strong random key in production. Without it, anyone with network access to port 8081 can execute arbitrary commands in containers.
• Sandbox isolation: Each chat session runs in a separate container with resource limits (2GB RAM, 1 CPU). On Docker Compose, containers use the standard runtime (runc) and share the host kernel. For stronger isolation, run the Kubernetes Helm chart with Kata Containers (hypervisor-grade, available today) — or, on Compose, switch to gVisor (see roadmap). Containers have network access by default.
• POSTGRES_PASSWORD: Change the default password in .env for production.

Known limitations

• Unauthenticated file/preview endpoints: /files/{chat_id}/, /api/outputs/{chat_id}, /browser/{chat_id}/, /terminal/{chat_id}/ — accessible to anyone who knows the chat ID. Chat IDs are UUIDs (hard to guess but not a real security boundary).
• No per-user auth on server: The MCP server trusts whoever sends a valid MCP_API_KEY. User identity (X-User-Email) is passed by the client but not verified server-side.
• Credentials in HTTP headers: API keys (GitLab, Anthropic, MCP tokens) are passed as HTTP headers from client to server. Safe within Docker network, but use HTTPS if exposing externally.
• Default admin credentials: admin@open-computer-use.dev / admin — change immediately in multi-user setups.

Security roadmap

We plan to address these in future releases:

• Per-session signed tokens for file/preview/terminal endpoints (replace chat ID as auth)
• Server-side user verification via Open WebUI JWT validation
• HTTPS support with automatic TLS certificates
• Audit logging for all tool calls and file access
• Network policies for sandbox containers (restrict egress by default)
• Secret management — move credentials from headers to encrypted server-side storage
• gVisor (runsc) runtime — optional container sandboxing for stronger isolation (like Claude.ai)

Ideas? Open a GitHub Issue. Want to contribute? See CONTRIBUTING.md or reach out on Telegram @yambrcom.

Development

# Build workspace image locally
docker build --platform linux/amd64 -t open-computer-use:latest .

# Run tests
./tests/test-docker-image.sh open-computer-use:latest
./tests/test-no-corporate.sh
./tests/test-project-structure.sh

# Build and run full stack
docker compose up --build

Contributing

See CONTRIBUTING.md. PRs welcome!

Community

• Managed hosting: yambr.com — cloud version by the maintainers (chat.yambr.com for the free demo, app.yambr.com for API keys, docs.yambr.com for the cloud docs)
• Issues & Ideas: GitHub Issues
• Telegram: @yambrcom

License

This project uses a multi-license model:

• Core (computer-use-server/, openwebui/, settings-wrapper/, Docker configs): Functional Source License, Version 1.1, Apache 2.0 Future License (FSL-1.1-Apache-2.0). Free to use, modify, fork, redistribute, and self-host internally. Each release automatically converts to Apache 2.0 two years after publication. Offering a hosted or embedded service that competes with our paid version(s) requires a commercial agreement.
• Our skills (skills/public/describe-image, skills/public/sub-agent): MIT
• Third-party skills: see individual LICENSE.txt files or original sources.

Attribution required: include "Open Computer Use" and a link to this repository.

See NOTICE for details. For third-party dependency licenses (PyMuPDF AGPL, Anthropic Skill License, Apache 2.0 bundles, etc.), see THIRD-PARTY-LICENSES.md.