leblancfg/code-mcp
3.2
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An MCP (Model Context Protocol) server that provides code interpretation capabilities via Google Cloud Functions.
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