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mcp-server-jupyter

Verified Safe

by 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

Run Command
mcp-jupyter --transport websocket --port 3000 --idle-timeout 600

Environment 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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Stats

Interest Score33
Security Score9
Cost ClassMedium
Avg Tokens500
Stars1
Forks0
Last Update2026-01-19

Tags

JupyterAI AgentsData ScienceAPIPythonStatefulSecureObservability