MCP Dev Summit Bengaluru 2026

Jupyter notebooks are essential for AI agents, yet the .ipynb JSON format is token-heavy and fragile for LLM manipulation. While an MCP server seemed like the obvious solution, we instead built nb—an open-source Rust CLI designed for agentic workflows.

This talk explores the design decisions behind nb and our move away from standard tool schemas:
- The Sentinel Format: Why line-oriented @@cell and @@output sentinels outperform deeply nested JSON for agent comprehension.
- Token Efficiency: How a single 800-token skills file replaced a complex MCP implementation, drastically reducing overhead.
- Content Hashing: Using SHA256 to solve output externalization and state management.
- Real-time Sync: Demonstrating collaborative editing via Y.js when bridged to a Jupyter server.

We’ll share benchmarks on task completion rates and token costs, and provide a clear framework for choosing between MCP servers and CLI-based skills. Attendees will learn when to leverage the simplicity of a CLI and when MCP’s multi-tenant auth and discovery are truly necessary.