The 10 MCPs every user researcher should connect to Claude and how to use them
The integrations I'd install first if I were starting today, with worked examples for every one
👋 Hey, I’m Nikki. Each week I write about UX research strategy, communicating impact, and using AI to do your best work. For more: Claude Skills Bundle | Claude Agents | AI Prompt Library | Team Training | AI Courses for UXRs
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For a long time, I treated Claude like the world’s most expensive copy-paste machine.
Every research project started the same way. I’d open up a new chat, and then I’d start pasting things in: the PRD from Confluence, the Figma prototype URL (which Claude couldn’t actually open back then, but I tried anyway), three Slack threads from #product, the half-finished brief I’d cobbled together in Notion, last quarter’s research report, a handful of customer quotes I’d pulled out of past interview transcripts, the discussion guide template I always use, and a couple of stakeholder emails for context.
By the time Claude had enough background to be useful, I’d already done about forty minutes of work, most of which I’d have to repeat the next time I started a fresh chat.
I knew there had to be a better way, I just didn’t have the language for it yet.
Then I started learning about MCPs, and the way I work with Claude shifted completely.
If you’ve been using Claude for research work and you keep running into the same friction (the context-pasting, the “Claude can you find that thing I mentioned three chats ago”, the wishing your AI assistant could just see your Jira board), this article is for you. I’m going to walk you through the ten MCPs I think every user researcher should know about, with worked examples for each, and the order I’d install them if I were starting over today.
What an MCP is
MCP stands for Model Context Protocol. The simplest way I’ve found to describe it is that an MCP is a bridge that lets Claude reach into a tool you already use without you having to copy-paste anything in.
Before MCPs, if I wanted Claude to help me synthesise findings from a study, I had to manually export the transcripts from Zoom, paste them into the chat one by one, then ask my question. Now, I can connect Zoom once, and Claude can pull the transcripts directly. The first time it worked, I felt like I’d unlocked a cheat code.
Every MCP exposes a set of tools that Claude can use on your behalf. The Slack MCP exposes tools like “search messages” and “send a message”. The Google Drive MCP exposes tools like “search files” and “read document”. The Zoom MCP exposes tools like “search meetings” and “get transcript”. You don’t have to know exactly which tools are available, you just ask Claude in plain language what you want, and it figures out which tools to call.
The thing I want you to take away: MCPs turn Claude from a smart chat partner into something closer to a colleague who has access to your actual work. The shift is bigger than it sounds.
What this unlocks for user researchers in particular
I think MCPs are useful for almost any knowledge worker, but I’d argue they’re especially valuable for UXRs because of how our work is shaped.
We pull from a lot of disconnected places. The PRD lives in Confluence or Notion. The prototype lives in Figma. The customer quotes live in a Google Doc transcript, or a research repository, or a Zoom recording someone hasn’t watched yet. The stakeholder context lives in Slack. The participant pipeline lives in a recruitment tool or a spreadsheet. The product roadmap lives in Linear or Jira. The voice of the customer signal lives in Intercom or Zendesk. The deliverables live in Google Drive.
When I was the first and only UXR at a hospitality platform years ago, I used to keep what I called my “research brain trust” tab group, a row of about fifteen browser tabs I’d open at the start of every project just so I could ping-pong between them. I’d spend the first hour of every kickoff just refreshing my memory on what was already known. That’s research work I’d have loved to automate, and that’s exactly the kind of context-gathering MCPs make trivial.
I also think there’s a second reason MCPs matter for us. Research is one of the most context-dependent jobs in a product org. A finding from one study is only as useful as your ability to connect it to what’s being built, what was previously researched, what stakeholders are worried about, and what users are asking for. MCPs let Claude actually do that connection work, instead of you doing it manually every time.
Paid subscribers, this is where the deep walkthrough starts.
If you’ve felt the copy-paste fatigue, the “Claude doesn’t know my world” fatigue, the “I wish my AI could just look at my Jira tickets” fatigue, this is the part that’s going to save you hours every week.
Below, I walk you through the ten MCPs I’d install in the order I’d install them, with worked examples for each:
Zoom (how to turn a folder of interview recordings into a pattern map in under an hour)
Notion (how to query your team wiki and stop hunting for old PRDs)
Google Drive (how to use transcripts and old reports as live context, not dead files)
Atlassian, Jira and Confluence (how to prep for a kickoff in five minutes instead of an hour)
Slack (how to mine stakeholder context without scrolling for two days)
Gmail (how to handle participant outreach without sounding like a robot)
Google Calendar (how to schedule a cohort of interviews without losing your mind)
Linear (how to link research findings directly to the feature pipeline)
Figma (how to use the prototype as live context for your discussion guide)
Intercom (how to mine support data for research questions you didn’t know you should be asking)
Plus the mistakes I’ve made setting these up (so you don’t have to), and a three-step starter approach you can run this week.
If “I should set Claude up better but I never have time” has been the thing on your list for six months, this is the path I’d follow.
Exclusively for paid subscribers
