AI assistants have become part of daily work for drafting, research, summarizing. Performance data hasn't kept pace. Checking on goal progress, recognition, or team performance still means logging into a separate platform, running a report, or asking HR to pull one.
Getting a straight answer about goal progress, team recognition, or who's overdue for a check-in still means logging into a platform, running a report, or asking HR to pull one. That's friction on a question that should take seconds to answer.
Betterworks MCP Server, now in beta, closes that gap. It brings Betterworks performance intelligence directly into ChatGPT, Claude, and any MCP-compatible AI tool — no logins, no exports, no new dashboard to learn.
What is the Betterworks MCP Server?
MCP stands for Model Context Protocol — a standard that lets AI assistants like ChatGPT and Claude securely connect to approved business systems. Think of it as a bridge, not a new product to learn.
With Betterworks MCP, approved users can:
Ask questions about goals, teams, users, recognition, and related performance context, right from ChatGPT or Claude
Get answers in natural language instead of navigating the platform or building a report
Access only the Betterworks data they already have permission to see
The beta is read-only — you can ask questions and get answers, but you can't yet take action in Betterworks from your AI tool. That's coming. For now, it's scoped to goals, teams, users, recognition, and hashtags, with write capability planned for the winter GA release.
AI-powered performance insights without manual reporting
It's easy to hear "AI integration" and assume this is a feature for your IT team. It's not. This is about closing the gap between having performance data and actually using it.
Get faster answers from performance data. Ask about goal progress, recognition, and team activity in plain language instead of pulling a report or waiting on HR.
Prepare better for performance conversations. Walk into a 1:1, check-in, review, or leadership update already knowing where things stand — goal progress, recent recognition, what's stalled, what needs attention.
Spend less time gathering data and more time acting on it. Combine Betterworks data with whatever else is already in your AI workflow instead of manually exporting reports or piecing information together across tools.
That last point is the real shift. Most organizations have performance data. Few can use it in the moment they need it — before a 1:1, during a leadership review, in the middle of a planning conversation. MCP closes that gap.
What you can ask Betterworks MCP today
The best way to understand the value is to see the kinds of questions it answers. A few examples from beta customers:
"What's the latest progress on Sarah's Q3 goals?" — a quick pulse-check without opening the platform.
"Create a brief of goals at risk for the Product team this quarter, including goals that are behind or haven't been updated recently." — the kind of prep work that used to take an hour, done in seconds.
"Prepare a 1:1 summary for Jordan, including goal progress, recent recognition, and areas I should follow up on." — walk into the conversation prepared instead of scrambling beforehand.
"Summarize recognition patterns for the Customer Success team this quarter, including who's been overlooked." — surface the gaps that are easy to miss when recognition happens informally.
"Create a leadership update for Marketing, including goal progress, at-risk goals, and recommended follow-up areas." — go from raw data to a narrative leaders can actually use.
None of these require a dashboard. They require a question, asked in the place you already work.
Built on performance intelligence, not a chatbot layer
An AI assistant is only as good as what it can see. Plenty of tools can layer a chatbot on top of thin, episodic data. Betterworks was built around continuous performance — goals, feedback, recognition, and check-ins captured as work happens, not reconstructed months later. That's what makes the answers MCP gives you meaningful instead of generic.
This is why we see MCP as a capability of Talent Intelligence, not a standalone feature. The richer the performance data underneath it, the more useful the questions you can ask on top of it.
Secure, permission-aware access to your performance data
Bringing performance data into AI tools raises a fair question: who can see what? Betterworks MCP enforces our native permission model. Users only access the data they already have permission to see inside Betterworks. There are no new access controls to configure and no risk of over-sharing. Your organization keeps the same security posture it has today — the data just becomes reachable from where work already happens.
Get started with Betterworks MCP
Betterworks MCP Server connects to ChatGPT, Claude, and any MCP-compatible AI tool. If you're a current customer interested in joining the beta, or a prospect who wants to see it firsthand, talk to your Betterworks contact or request a demo.
See how Betterworks MCP brings performance data into the tools your team already uses.
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