Nordic Semiconductor just shipped MCP servers that give AI assistants direct access to nRF Connect SDK documentation, API references, device configurations, and live fleet data from nRF Cloud. The constraint being removed is not AI in the IDE. It is SDK documentation being a static corpus that AI tools cannot query reliably, forcing engineers to paste context manually or accept hallucinated answers about board bring-up, DeviceTree, and Kconfig.
The mechanism matters: Nordic's MCP servers expose validated, primary-source context directly to Claude Code, Cursor, GitHub Copilot, or any other AI agent. The model sees the actual SDK docs, not a stale training snapshot or a web-scraped fragment. That changes the error class. Instead of getting a confident wrong answer about an nRF54L20 register, the agent has the correct reference at query time. Nordic also claims lower token cost per query compared to pumping raw documentation into a generic LLM context window, because the specialized model surfaces only the relevant slice.
The honest caveat is that this is still supervised tooling, not autonomous firmware generation. The CNX Software writeup notes the agent added spurious peripherals in a demo, which had to be corrected by the engineer. You have to be specific, technical, and review the output. That is not a knock; it is the current ceiling of agentic firmware work. The meaningful shift is that the tool now fails on plausible-but-wrong grounds rather than fabricated-from-thin-air grounds, which is a shorter debug cycle.
Embedded SDK vendors who have not done this yet are one migration cycle behind. The pattern is replicable: expose your documentation, configuration schemas, and field telemetry as MCP context, and your SDK becomes the primary-source grounding layer for every AI workflow your customers run. The vendors that do this first lock in the AI-assisted development loop. Nordic just moved the embedded wireless stack to the front of that line.