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UN System Data Commons is a public platform that connects statistics from across the United Nations system in a searchable knowledge graph. The new data.un.org launched on September 17, 2026 with natural-language search, while the underlying Google Data Commons ecosystem offers an MCP server that lets compatible agents explore statistical data. The important promise is not “ask anything and get a final answer.” It is a shorter path from a question to a candidate indicator, its place and time coverage, the original source, and a reviewable table. This guide separates the public website workflow from the MCP workflow and covers exact setup locations, completion checks, limitations, security, and three practical use cases. What changed International statistics have traditionally been spread across agency portals, spreadsheets, naming systems, and geographic definitions. UN System Data Commons connects those relationships so that a user can search by topic or place and inspect charts...

A research paper can describe a useful method in a few pages, yet applying it to your own data may require hours of repository hunting, dependency setup, notebook editing, and result checking. Paper2Agent is an open project designed to close that gap. It converts papers into agent-readable skills and turns supported research repositories into tested Model Context Protocol tools. It is not a “drop in any PDF and get an authoritative scientist” service. The Paper2Agent study, published in Nature on September 16, 2026, reports that a substantial fraction of repositories still could not be agentified because of incomplete code, missing documentation, or environments that could not be resolved. This guide uses the official repository and paper as checked on September 19 to explain how to install the project for Codex or Claude Code, choose the right conversion route, and decide whether the result is ready to use. At a glance A paper-only input becomes a searchable paper skill ; an e...