Hex vs Deepnote
Side-by-side trajectory, velocity, and editorial themes.
Hex is remaking its notebook into an agent that both uses and plugs into MCP
Hex is converting its analytics notebook into an AI agent platform. It now runs as an MCP client, is invocable from Codex, and ships generative data apps built from prompts, while keeping its model roster current with Kimi K2.7 and Fable 5 and giving admins default-model and branding controls. Integration and governance work — a Figma connector, AWS IAM-role support, signed embedding — rounds out the core.
The arc points at Hex as connective agent infrastructure: consuming external context and tools via MCP, distributing itself into other agent surfaces like Codex, and letting analysts assemble apps and dashboards from prompts. Expect the agent, rather than the notebook grid, to become the primary interface, with model choice and governance layered on top.
Likely next steps deepen the agent's tool-use over MCP connections and push generative apps further toward production embedding and governance controls.
Deepnote reshapes the data notebook into agent-operable infrastructure.
Deepnote, a collaborative data-science notebook, is steadily making itself agent-native: MCP tools now let AI agents create and wire integrations end-to-end, and OpenAI's Codex connects natively to a Deepnote workspace's notebooks, schedules, and data. Underneath, it keeps shipping solid workflow features — run snapshots, Git and GitLab sync, Polars, PDF export.
Two tracks are converging: reproducibility and engineering rigor (immutable run snapshots, Git sync, notebook interoperability) and agent-operability (MCP tools, Codex context). Deepnote is positioning the workspace as the trusted context layer that AI agents act through, not just a place humans write notebooks.
Expect more MCP tooling that lets agents operate Deepnote projects autonomously, plus deeper native hooks for external coding agents — the workspace-as-agent-context bet will likely expand beyond Codex.
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