32 lines
1.3 KiB
Markdown
32 lines
1.3 KiB
Markdown
# mcp-sandbox
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Ephemeral, minimalist Python sandbox for MCP-driven code execution (plotting, quick analysis, exfil-style external fetches with `curl`/`wget`/`httpx`).
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## What's baked in
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- Debian slim + uv + Python 3.13 (rebuild image to bump)
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- Sci stack: numpy, pandas, matplotlib, plotly, seaborn, scipy, scikit-learn
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- HTTP: requests, httpx, curl, wget
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- Tools: git, ssh, ipython, sudo
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- Non-root user `coder` (uid 1000) with passwordless sudo
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## Why "baked in" vs install-at-startup
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MCP spawns short-lived workspaces. Installing deps every time burns ~2 min and ~300 MB of network. Bake them, spin in ~3 s.
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## Build the image (run on CT 111)
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```bash
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cd /opt/stacks/coder/templates/mcp-sandbox
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docker build -t coder-mcp-sandbox:latest .
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# bump Python: docker build --build-arg PY_VERSION=3.14 -t coder-mcp-sandbox:latest .
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```
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## Push the template to Coder
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```bash
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coder templates push mcp-sandbox -d /opt/stacks/coder/templates/mcp-sandbox
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```
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## Ephemerality
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`$HOME` is **not** persisted. Each workspace start gets fresh state. Plots written to `~/plots/` vanish on stop — copy via `coder cp` or upload elsewhere from inside the workspace if you need to keep them.
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## GPU
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`/dev/dri/renderD128` is mounted. Useful if matplotlib offloads to GPU or if you decide to add `torch[cpu]` → `torch` with Arc support later.
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