Lab Virtual MCP Server

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.