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Comparison · Analytics

Apify vs Deepnote

Side-by-side trajectory, velocity, and editorial themes.

A
Apify
ANALYTICS
7.5

Apify retools Actors for the agentic web — agent payments and login-gated MCP access.

◆ Current state

Apify runs a marketplace of 'Actors' — hosted scrapers and automations — and its recent releases aim squarely at AI agents as the new consumer. Agents can now pay per run in USDC via the x402 protocol with no account, reach login-gated apps through MCP connectors, and discover Actors through SEO-friendly published task pages. In parallel, Apify is tightening Actor permissions as agents run more code on users' behalf.

◆ Where it's heading

Apify is repositioning from a developer scraping platform into agent-native infrastructure: making Actors callable, payable, and discoverable by autonomous agents, while adding the permission guardrails that agent-driven execution demands. Security defaults are the necessary counterweight to opening the platform to agents.

◆ Prediction

Expect more agent-economy plumbing — broader x402/agentic-payment coverage and more MCP-connected apps — alongside continued least-privilege permission tightening as the default execution model becomes agent-initiated.

D
Deepnote
ANALYTICS
6.3

Deepnote reshapes the data notebook into agent-operable infrastructure.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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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