Best practices for working with remote/local code Repo with MCP Connectors & Developer Mode
Hi OpenAI Team and Community,
With the recent rollout of MCP (Model Context Protocol) support in ChatGPT Web / Developer Mode, we’ve seen a surge in users connecting their local repositories to GPT-5.5/Pro models, so I’ve been developing an MCP runtime called coding-tools-mcp since May.
My question is regarding the official stance on “Agentic Safety” for local/remote coding tools:
In my project, I’ve implemented Linux Landlock and Docker sandboxing to ensure the model cannot perform destructive operations or leak sensitive .env files, even if prompted.
- Does OpenAI have specific security guidelines for third-party MCP connectors accessing local/remote filesystems?
- Is there a preferred “Semantic Tool” pattern (e.g., using apply_patch vs. raw bash) that OpenAI recommends for better model alignment?
I believe that for MCP to be a viable professional tool, we need to move past simple “wrappers” and move toward secure, stateful runtimes. I’d love to get feedback on the architecture I’ve built: GitHub: xyTom/coding-tools-mcp Docs: coding-1afcb9be.mintlify.app
Looking forward to your thoughts!
Discussion in the ATmosphere