Secure Agent Workspace

Name: Secure Agent Workspace
Author: HrRodan

@HrRodan

リポジトリ

Secure Agent Workspace について

A sandboxed, agentic workspace providing secure filesystem, bash, and uv-powered Python execution.

#python #uv #docker #coding

基本情報

カテゴリ

AI とエージェント

ランタイム

python

トランスポート

stdio

公開者

HrRodan

投稿者

Martin

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "agent-workspace-mcp": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "--init",
        "--memory=2g",
        "--cpus=2.0",
        "--pids-limit=256",
        "--cap-drop=ALL",
        "--security-opt=no-new-privileges:true",
        "--read-only",
        "--tmpfs",
        "/tmp:size=64m",
        "--tmpfs",
        "/home/mcpuser/.cache:size=512m",
        "--user",
        "1000:1000",
        "-v",
        "/path/to/your/projects:/workspace",
        "ghcr.io/hrrodan/agent-workspace-mcp:latest"
      ]
    }
  }
}

ツール

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概要

What is Secure Agent Workspace?

Secure Agent Workspace is a Model Context Protocol (MCP) server that provides a highly secure, containerized workspace for LLM agents. It allows agents to autonomously code, test, and debug in an isolated Docker sandbox, protecting the host machine.

How to use Secure Agent Workspace?

Pull or build the Docker image, then configure your MCP client (e.g., Claude Desktop) with a docker run command that includes resource limits, security options, and a volume mount to your project directory. Alternatively, use the OpenAI Agents SDK with an MCPServerStdio to invoke the server programmatically. Environment variables such as COMMAND_TIMEOUT and LOG_LEVEL can be set via Docker --env.

Key features of Secure Agent Workspace

Full project lifecycle (uv init, add, run)
Secure bash execution with timeouts
Token-optimized output via RTK (60–90% savings)
Path-traversal protected filesystem operations
Multi-layer security (non-root, dropped capabilities, read-only)
Precision editing with fuzzy matching and syntax validation

Use cases of Secure Agent Workspace

Agents autonomously create, test, and debug code in a sandboxed environment
Manage project dependencies using uv add and uv run
Perform precise file edits with syntax validation to prevent broken code
Search workspace for files using glob patterns, excluding high-noise directories