open-computer-use MCP Server
Yambr/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.
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
Yambr/open-computer-use is a Python MCP server. 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. Topics: agents, claude-code, computer-use, llm, mcp-server, openwebui, skills.
Ranked #3077 out of 29331 indexed tools.
Actively maintained with commits in the last week.
Ecosystem
Score Breakdown
35 stars → early stage
Last commit 1d ago → actively maintained
0/4 issues closed → many open issues
4 contributors → small team
No dependents → no downstream usage
Weights: Freshness 25% · Issue Health 25% · Dependents 25% · Stars 15% · Contributors 10% · How we score →
How to Improve
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From the README
# 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. ## 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 owRead full README on GitHub →
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