mcp-server-jupyter
Verified Safeby davidwarshawsky
Overview
Transforms Jupyter notebooks into a reliable, stateful, and secure backend API for AI agents, facilitating data analysis, scientific computing, and visualization through controlled execution and inspection.
Installation
mcp-jupyter --transport websocket --port 3000 --idle-timeout 600Environment Variables
- MCP_SESSION_TOKEN
- MCP_PACKAGE_ALLOWLIST
- MCP_STRICT_MODE
- MCP_ALLOWED_ROOT
- MCP_MAX_KERNELS
- MCP_MEMORY_LIMIT_BYTES
- MCP_DATA_DIR
- OTEL_EXPORTER_OTLP_ENDPOINT
- LOG_LEVEL
- MCP_PORT
- MCP_HOST
Security Notes
The server implements comprehensive security measures including Pydantic-validated input, robust Docker sandboxing (seccomp, capability dropping, read-only rootfs, network isolation), entropy-based secret redaction, structured audit logging, atomic notebook writes, and backpressure for DoS prevention. It also features UUID-based zombie kernel reaping and explicitly removed insecure checkpointing mechanisms. Token-based authentication (MCP_SESSION_TOKEN generated at runtime) is enforced, and a configurable package allowlist (MCP_PACKAGE_ALLOWLIST) prevents supply chain attacks. Path traversal is strictly prevented for both notebook and asset access. While highly hardened, the 'auto_analyst' prompt example, if executed literally by an agent, might bypass the server's package allowlist by directly using `subprocess.check_call` for `pip install`, though the dedicated `install_package` tool is secure.
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