execution in a secure and scalable lab setup.
⚙️ Lab Virtual MCP Server (Execute Code Remotely via Claude AI)
Create a virtual lab for users to run custom code remotely using the Model Context Protocol (MCP) and integrate with Claude AI or other clients.
<img src="video/test.gif" alt="description" height="300" width="900" />
🔗 GitHub Repo
<pre>
📦 https://github.com/Nuvepro-Technologies-Pvt-Ltd/McpSever_Remote_code_execution.git
</pre>
📂 This repo has moved to base/base-mcp
🚀 What This Lab Server Does
🧠 Enables remote Python code execution through cline AI
🧪 Supports real-time lab scenarios (code evaluation, sandbox testing, etc.)
📋 Prerequisites
Ensure you have the following on your system:
✅ Python 3.10.11
✅ pip (Python package manager)
✅ fastmcp (to serve the MCP endpoint)
✅ uv (virtual environment manager, via scoop or curl)
✅ Access to Claude Desktop or Cursor or cline (for testing)
🧱 Installation Steps
1. Clone the MCP Server Repo
<pre>
git clone https://github.com/Nuvepro-Technologies-Pvt-Ltd/McpSever_Remote_code_execution.git
</pre>
2. Set up Python Environment
<pre>
Set-ExecutionPolicy RemoteSigned -Scope CurrentUser
</pre>
<pre>
scoop install python
</pre>
<pre>
scoop install uv
</pre>
cd McpSever_Remote_code_execution
3. Set Up Virtual Environment
<pre>
python -m venv .venv
</pre>
<pre>
.\.venv\Scripts\activate # Windows
</pre>
<pre>
source .venv/bin/activate # macOS/Linux
</pre>
4. Install Dependencies
<pre>
pip install fastmcp
</pre>
<pre>
pip install cryptography
</pre>
<pre>
pip install shelve
</pre>
5. Run the Server
<pre>
fastmcp run app.py
</pre>
You now have a remote code execution server listening for requests via MCP.
🧪 MCP Client Configuration
For Claude Desktop / Cursor, update your mcp_config.json:
<pre>
{
"mcpServers": {
"CloudlabMcp": {
"disabled": false,
"timeout": 500,
"type": "stdio",
"command": "uv",
"args": [
"run",
"--with",
"fastmcp",
"python",
"%PROJECT_PATH%\\app.py"
],
"env": {
"API_KEY": "your_private_key",
"Baseurl": "your seed phrase here",
"compnaykey": "your_private_key"
},
"autoApprove": [*]
}
}
}
</pre>
Beofre start Mcp set path
<pre>
set PROJECT_PATH=D:\YourProject
</pre>
<pre>
cline run CloudlabMcp
</pre>
✅ Available Tools (Prebuilt in MCP)
Tool Description
execute_code Executes user-provided Python code
💡 Recommendations for Lab Admins
✅ Add sandboxing logic to app.py if users can run arbitrary code.
✅ Use Docker or subprocess isolation for safer execution (optional).
✅ Monitor logs and set execution timeouts.
