What runtime environment does Secure Agent Workspace require?
The server runs inside a Docker container. The host needs Docker Engine, and the container image can be pulled from GHCR or built locally.
@HrRodan
A sandboxed, agentic workspace providing secure filesystem, bash, and uv-powered Python execution.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"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"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
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.
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.
uv add and uv runThe server runs inside a Docker container. The host needs Docker Engine, and the container image can be pulled from GHCR or built locally.

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