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Description from the maker (original English)
A sandboxed, agentic workspace providing secure filesystem, bash, and uv-powered Python execution.
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We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
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You need
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"agent-workspace": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/hrrodan/agent-workspace-mcp:1.4.134"
]
}
}
}Run this in your terminal
claude mcp add agent-workspace -- docker run -i --rm ghcr.io/hrrodan/agent-workspace-mcp:1.4.134Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"agent-workspace": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/hrrodan/agent-workspace-mcp:1.4.134"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"agent-workspace": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/hrrodan/agent-workspace-mcp:1.4.134"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
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Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026
The registry name was verified with the GitHub account HrRodan, which owns the repo
We have not read this repo from GitHub yet
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This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
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It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (1.4.134) reached the registry 6 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.
In the same category: GitHub, Desktop Commander, Cloudflare MCP
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MCP server for terminal commands, file operations, and process management
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A unified Model Context Protocol (MCP) server providing a highly secure, containerized workspace for Large Language Models (LLMs). It acts as an isolated "agentic playground" where agents can autonomously code, test, and debug without risking the host machine.
uv init, manage dependencies with uv add, and execute via uv run.run_bash outputs (like ls, git, and test runners), saving 60-90% of LLM context tokens.search_and_replace with fuzzy whitespace matching, indentation preservation, dry-run support, and syntax validation for Python, JSON, JSONL, TOML, and YAML.flowchart TD
Client["MCP Client (Claude / Cursor)"] -- "stdio (JSON-RPC)" --> FastMCP["FastMCP Server"]
subgraph Sandbox ["Docker Sandbox Container (mcpuser)"] direction TB
FastMCP -. "Intercepts accidental prints" .-> StdioGuard["StdoutRedirector"] FastMCP -. "Application Logs" .-> Logger["Dual Logger (stderr & .mcp/server.log)"]
FastMCP -- "Tool Calls" --> SecurityGuard["Security & Path Validator"]
subgraph Toolset ["Tool Modules"] direction TB SecurityGuard --> FSTools["Filesystem (read, write, list, search)"] SecurityGuard --> EditTools["Editing (search_and_replace)"] SecurityGuard --> ExecTools["Execution (run_bash)"] end
EditTools -- "AST Verification" --> Validator["Syntax Validations (Python, JSON, JSONL, TOML, YAML)"] ExecTools -- "Process Group (Timeout=60s)" --> Shell["/bin/sh Subprocess"] Shell -- "Package Mgt & Checks" --> UV["uv Environment / Ruff"]
FSTools -- "Secure I/O" --> Workspace["/workspace Directory"] EditTools -- "Atomic Writes" --> Workspace Shell -- "Executes within" --> Workspace end
Workspace <--"Volume Mount"--> HostFS["User Host Filesystem"]
# Pull from GHCR
docker pull ghcr.io/hrrodan/agent-workspace-mcp:latest
docker build --build-arg UID=$(id -u) --build-arg GID=$(id -g) -t agent-workspace-mcp .
Here is a quick boilerplate showing how to use the containerized workspace programmatically using the standard openai-agents SDK:
import asyncio
from agents import Agent, Runner from agents.mcp import MCPServerStdio
async def main():
server = MCPServerStdio( name="Sandboxed Workspace", params={ "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", # Replace with your host UID:GID "-v", "/path/to/your/projects:/workspace", "ghcr.io/hrrodan/agent-workspace-mcp:latest", ], }, client_session_timeout_seconds=60.0, )
with open("skills/agent-workspace-mcp/SKILL.md", "r") as f: skill_instructions = f.read()
agent = Agent( name="WorkspaceAgent", instructions=f"You are a coding agent with access to a secure workspace.\n\n{skill_instructions}", mcp_servers=[server], )
async with server: result = await Runner.run( agent, "Create a python script in the workspace to print the first 10 Fibonacci numbers, then run it." ) print(f"Agent's Final Output:\n{result.final_output}")
if name == "main": asyncio.run(main())
Add the following configuration to your claude_desktop_config.json or Cursor settings.
{
"mcpServers": { "agent-workspace-mcp": { "command": "docker", "args": [ "run", "-i", "--rm", "--init", // "--network", "none", // Network Isolation (optional) - see below "--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" ] } } }
[!IMPORTANT]
Linux Users: Replace
1000:1000with your actual UID:GID (runid -uandid -g). Claude Desktop does not expand environment variables.
Signal Handling: The
--initflag is essential for proper signal forwarding and zombie process reaping.
| Tool | Description |
|---|---|
read_file | Read text files with optional offset and limit (default: 100 lines). |
write_file | Create files with syntax validation and a 5MB size guard. Refuses to overwrite existing files by default (create_only=True). |
list_directory | List contents with [F]ile and [D]irectory prefixes. |
search_workspace | Find files by glob pattern with support for exclude_patterns. |
run_bash | Execute shell commands in /workspace with a 60s timeout. Automatically optimized via RTK to reduce token usage. |
search_and_replace | Multi-edit tool with fuzzy whitespace matching, indentation preservation, dry-run mode, and syntax validation (Python, JSON, JSONL, TOML, YAML). |
The server supports the following environment variables (passed via Docker --env):
| Variable | Default | Description |
|---|---|---|
COMMAND_TIMEOUT | 60 | Default seconds before run_bash kills a process. |
MAX_SEARCH_RESULTS | 50 | Maximum results returned by search_workspace. |
MAX_READ_SIZE_BYTES | 1048576 | Maximum file size for read_file (1MB). |
MAX_WRITE_SIZE_BYTES | 5242880 | Maximum file size for write_file (5MB). |
LOG_LEVEL | INFO | Python logging level (DEBUG, INFO, etc.). |
This server employs a defense-in-depth strategy, explicitly separating strict security boundaries from developer experience and operational reliability features.
These features are designed to protect the host system and enforce strict isolation boundaries.
--cap-drop=ALL), neutralizing privilege escalation vectors./app directory containing the server source and its virtual environment is owned by root and read-only for the mcpuser. This prevents the server from modifying itself or being tampered with via run_bash.no-new-privileges:true to prevent any process from gaining elevated rights./workspace.Features focused on seamless integration, usability, and reducing friction during agentic workflows.
mcpuser with UID/GID customizable at build time, eliminating tedious file permission conflicts on host volume mounts.run_bash are transparently rewritten through RTK to provide ultra-compact, LLM-friendly output without altering underlying command behavior..git, .venv) are automatically ignored to keep context windows lean and relevant.--rm), guaranteeing a clean, predictable slate for every new session without state leaking across connections.Features ensuring the structural integrity of the workspace and providing observability.
write_file and search_and_replace perform in-memory syntax validation for Python, JSON, JSONL, TOML, and YAML before persisting changes, preventing broken code states.write_file blocks accidental overwrites of existing files by default and enforces a 5MB size guard to prevent workspace flooding.By default, the container has full network access via Docker's bridge network. For maximum isolation, you can completely disable the network stack using --network none:
docker run -i --rm --init \
--network none \ --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
This creates a fully air-gapped sandbox — only the loopback interface exists inside the container. All outbound connections (curl, DNS, uv add, etc.) will fail immediately, eliminating data exfiltration and lateral m
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