Code MCP Server

An MCP (Model Context Protocol) server that provides code interpretation capabilities via Google Cloud Functions.

Features

Execute Python, JavaScript, and Bash code in a sandboxed environment
Automatic deployment to Google Cloud Functions
STDIO-based MCP server implementation

Prerequisites

Python 3.11+
Google Cloud SDK (gcloud) installed and configured
A Google Cloud Project with Cloud Functions API enabled

Installation

$ pip install -e ".[dev]"

Usage

You’ll first need to set up a Google Cloud Function that can execute code. The server will handle requests to this function. In this repo, run it with

$ uv run python deploy_gcf.py

As an MCP Server

$ uv run python main.py

Running Tests

$ uv run pytest

Testing with the MCP Inspector

You can use the CLI feature with

$ GCF_URL=$MY_COOL_GCF_URL \
npx @modelcontextprotocol/inspector@0.11.0 \
--cli uv run python main.py \
--method tools/call \
--tool-name run_code \
--tool-arg "code=print(1+1)" \
--tool-arg language=python \
| jq

Configuration

Set the GCF_URL environment variable to use an existing Cloud Function, otherwise the server will attempt to deploy one automatically.

$ export GCF_URL="https://region-project.cloudfunctions.net/code-interpreter"

Architecture

MCP Server: Handles tool requests from AI agents
Google Cloud Function: Executes code in an isolated environment
Supported Languages: Python, JavaScript (Node.js), Bash