GeMCP: a first look at what we're building

AI tools like Claude, ChatGPT, and Gemini have become part of how recruiting teams work. For many Gem customers, they're already a go-to for summarizing interview notes, drafting role descriptions, editing outreach, and making sense of pipeline data.

But there's a consistent bottleneck: context. AI is only as good as the information you give it — and getting that information means exporting data, hunting down notes, stitching together reports from different places, and then doing the mental work of connecting it all. By the time you have what you need, you've already spent the time you were trying to save.

We’re building GeMCP to change that. It’ll give AI tools direct, secure access to your Gem data — so instead of feeding your AI the context, it already has it. Your full recruiting picture, ready to work with.

Stop feeding your AI. Let it pull from Gem.

Model Context Protocol (MCP) is an open standard that lets AI tools connect directly to data sources, so instead of copying and pasting information into a chat window, your AI can pull it securely from the source. Think of it as a secure bridge between your recruiting data and the AI tools your team already uses.

Gem is building GeMCP to be that bridge for Talent Acquisition (TA) teams. When your AI has direct access to Gem's data, you stop answering its questions and start asking your own.

What your AI can do when Gem is the data source

Most AI tools are working with whatever context you hand them. GeMCP gives them something better: Gem's recruiting data, in full.

What makes GeMCP different is the depth of what Gem brings as a data source:

• Full-funnel data: Gem captures the entire recruiting lifecycle, from first reachout through offer-out, including CRM activity, outreach engagement, and candidate relationship history that a standalone ATS never sees.

• Proprietary benchmarks: Gem's annual recruiting benchmarks and outreach reports are some of the most-used resources in TA. Via MCP, teams will be able to apply that intelligence directly to their own pipeline, in real time.

• An all-in-one platform: AI is only as good as the context it has. Because Gem spans sourcing, CRM, pipeline management, and analytics, the intelligence it can surface is richer than that of any single-purpose tool.

A new way to work with your recruiting data

Here's what this looks like in practice, once your AI has access to Gem's data.

For TA leaders: Imagine asking your AI assistant to pull pipeline health across all open reqs, benchmark your passthrough rates against Gem's industry data, and flag where you're behind, all in one conversation. No dashboard-switching, no manual exports. The kind of strategic read that used to take a RecOps analyst an afternoon.

For recruiters: Imagine getting a daily brief on which candidates need your attention, which roles are stalling, and what your outreach data says about which sequences are actually working, surfaced in plain language, ready to act on.

These are the kinds of questions that become answerable when your AI has the full Gem picture.

Be the first to see it

GeMCP is currently in beta and launching this summer. We're not waiting for GA to share it — because we want recruiting teams in the room as we build it.

On June 23rd at 11 AM PT, we're hosting a live session with Andrew Hahn and Genevieve Sublette from Gem and Zackary Skelly, Head of Talent at Dragonfly Capital — a team already thinking about what this shift means for how recruiting works. We'll cover what MCP actually is, what it means for TA teams specifically, and show real examples of what becomes possible when your AI has the full Gem picture. Plus live Q&A.

Register here to join us on June 23rd.