My favorite tool for relieving friction from my AI workflows is Zapier MCP. It connects AI assistants to Zapier’s vast, secure integration network of 30,000+ actions across 8,000+ apps—so now, instead of, say, copy-pasting text I generate with Claude, I can ask Claude to add the content to a new row in a table, or append text to a Google Doc, and act across other tools. AI carries out the actions for me, and I never have to leave my chat window.
There are so many ways to apply Zapier MCP to your specific workflows. But I bet you knew that already. The hard part is knowing where to start when you have tens of thousands of actions at your disposal.
To give you a leg up, we put together these 11 use cases created and tested by Zapier employees, complete with prompt suggestions and one-click tool bundles to help you set things up fast. No matter which ones you try, you’ll be building on solid ground: Zapier MCP has already powered more than 1 million tool calls (and counting). Let’s dive in.
This article contains ideas for using Zapier MCP along with tool bundles. To get started with a tool bundle, just click the button—it only takes a few minutes to set up. For detailed instructions on setting up Zapier MCP, head to the feature guide.
Table of contents
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What is MCP?
MCP stands for Model Context Protocol. It’s an open standard that lets AI assistants connect to external tools and data. Think of it as a universal adapter: instead of your AI only being able to chat, MCP lets it actually do things, like send emails, update your CRM, and create tasks.
You could build your own MCP server—but that means writing and maintaining integrations for every app you want to connect. Or you could use Zapier MCP.
Why should I use Zapier MCP?
Zapier MCP is our implementation of the MCP standard. And with it, you get access to more than 8,000 apps and 30,000 actions. So instead of building integrations yourself over the course of months, you can instantly tap in to Zapier’s entire ecosystem, including any private integrations your team builds.
Zapier MCP is production-ready out of the box. Zapier handles authentication, API updates, and error handling, so you don’t have to. It also works with any AI assistant that supports MCP—including Claude, ChatGPT, and Cursor—so you can conduct actions inside your AI tool of choice.
Ways to use Zapier MCP
We’ve grouped these use cases into four categories:
The first two categories are best for developers and technical teams that want to stay in flow without context-switching between tools. The third works for anyone managing scattered information across platforms. The fourth is designed for sales and marketing teams—but the principles can be adapted to other workflows, too.
And if you’re just getting started with Zapier MCP? You can use these prompts as examples to help you structure your own prompts.
Streamlining software development
Developers, if you’re tired of jumping in and out of your editor, Git, issue trackers, and communication tools, these workflows are for you. They’re designed to keep you in flow by letting AI handle the coordination across your dev stack.
1. Clean up merged and closed Git branches
You want to delete local Git branches that have been on GitLab or linked to closed Jira tickets across all your repositories, saving you time from cross-referencing apps and reducing clutter.
What to prompt your AI assistant
Apps to connect: GitLab, Jira
2. Debug production issues without leaving your editor
You want to pull logs, traces, and bug reports into Cursor, find the root cause, and fix the code in one continuous flow—no switching back and forth between your logging tool and editor.
What to prompt your AI assistant
Apps to connect: Braintrust, GitLab, Jira, Slack
3. Ship full releases without touching your browser
You want releases to be simple and flow seamlessly across every step—including handling the Git log, tagging, opening a merge request, kicking off pipelines, and then making an announcement on Slack.
What to prompt your AI assistant
Apps to connect: GitLab, Slack
4. Get a morning engineering report
You want a prioritized view of your merge requests (complete with status, any recent feedback from reviewers, and action items for you) without having to poke around in GitLab or email notifications.
Note: The following is a power-user prompt. Feel free to simplify it based on your setup.
What to prompt your AI assistant:
Apps to connect: GitLab
Accelerating feature delivery
Whether you’re working solo or on a team, shipping features often means juggling tickets, code reviews, and documentation across multiple tools. These workflows help you move from idea to merged code faster.
5. Get a code review without waiting for a teammate
You want to get a second pair of eyes on your code after you finish a feature, but you don’t want to waste a teammate’s cycles on obvious issues—or check the branch locally to run it through AI.
What to prompt your AI assistant
Apps to connect: GitLab, Claude
6. Turn detailed tickets into working code without copy-pasting
You want to pull a Jira ticket into Claude Code, let it implement the changes, and review the work before you push.
What to prompt your AI assistant
Apps to connect: Jira, Claude Code
7. Go from ticket to merged PR without leaving your editor
You want to pull a ticket, generate a plan for review, build the feature, and open the merge request, all in one continuous flow.
What to prompt your AI assistant
Apps to connect: Linear, Notion, GitLab
Consolidating knowledge and research
If you’ve ever lost track of an important Slack thread, buried a crucial doc in your drive, or struggled to remember where you saved that one piece of research, these use cases are for you. They speed up the time it takes to build a searchable knowledge base.
8. Build a research assistant that knows your work
You want to pull Slack threads, docs, and research into a curated knowledge base you can chat with, so your AI has the context to give you useful answers.
What to prompt your AI assistant
Apps to connect: Slack, Google Docs, Coda
9. Design features with the right context
You want to pull all the things—strategy docs, ICP profiles, planning docs, Slack threads, relevant Jira tickets, user research, and more—into your AI chat before you start designing a feature, and when you’re done, turn your product requirements document into a properly formatted Jira ticket.
What to prompt your AI assistant
Apps to connect: Google Docs, Coda, Jira, Slack, Dovetail
Optimizing sales and outreach
Sales and marketing teams know the pain of piecing together context from different sources before every call or campaign. These use cases pull everything together so you can automate that prep work.
10. Prep for sales calls without tab hopping
You want your AI assistant to help you get ready for a sales call by pulling customer relationship manager data, email history, and meeting notes into one conversation, then create personalized outreach for you.
What to prompt your AI assistant
Apps to connect: HubSpot, Gmail, Google Calendar
11. Create landing pages without copy-pasting
You want to turn scattered product assets into polished landing pages that follow SEO best practices and come with meta descriptions and FAQs—all connected to your content management system and project tracker.
What to prompt your AI assistant
Apps to connect: Google Docs, Contentful, Airtable
Design your perfect Zapier MCP workflow
After much prompting and tinkering with AI, I think we’ve all learned that for more detailed work, generic AI workflows are useful up to a point. Zapier MCP can help by safely plugging real utility into your AI assistants, no matter what tools you or your team use.
To get started with Zapier MCP, jump into the MCP dashboard today.
