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
Basic information
A sandboxed, agentic workspace providing secure filesystem, bash, and uv-powered Python execution.
Add this server to your MCP-compatible client using the configuration below.
{
"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"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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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