By Anything AI can do… AI can do better with SparkToro.
We (and dozens of our customers) have detailed over and over how real audience data + AI tool prompts = marketing insight magic, so I won’t belabor the point here. But, I will, with great excitement, introduce an easier-than-ever way to complete that process without ever needing to leave your AI tool of choice.
Welcome to SparkToro’s MCP Server 👇
The full details and connection process can be found here: SparkToro MCP Documentation.
What Can SparkToro MCP + AI Tools Do?
Just about anything and everything you might have previously done by exporting a SparkToro CSV and providing instructions on an upload to your favorite AI tool can now be performed directly from the interface. That includes:
- Running new reports from a prompt
- Accessing your existing reports and report groups
- Pulling specific data from reports (e.g. a list of podcasts or demographic details about an audience)
- Comparing multiple reports, and/or sections within those reports
- Using AI crawling functionality to perform tasks based on the data from SparkToro’s audience research
Here’s an early use-case example to get you started…
This past weekend, I spent some time with a friend from Afar.com. Like many writers, one of her constant struggles is identifying gaps in what their audience wants to read/learn and what they haven’t yet (or recently) covered. Enter SparkToro’s MCP + Claude 👇
I started by connecting Claude to my SparkToro account, then used the prompt above to run a gap analysis between what people who visited Afar were searching for and prompting vs. what had recently been published on the site.
As Claude worked on the problem, it pulled data directly from SparkToro, visualized it, summarized, and categorized (with relatively high accuracy, though it still needs a human review):
Next, it showed the gap between content topics the site had covered and those the audience had searched for. I used the past quarter for both data sources, even though SparkToro is now updating on a monthly basis 😎
The output did a pretty good job surfacing opportunities, and I suspect the folks at Afar might find at least half of these useful in their next round of topic considerations. My recommendation would be to tweak the prompt more or be even more prescriptive in which columns of data to use (and how), but that’s because I’m preternaturally skeptical of AI output—it defaults to the average and the stereotypes. But, when fed real audience data, the quality goes up significantly, and the insights gleaned become personalized to *your* audience (rather than just the words most frequently found around other words on the web).
If this sounds exciting to you, make sure to visit the SparkToro MCP Documentation. There’s an easy walkthrough for setup (though I’ll admit I found it SO easy to connect to Claude, I didn’t even use the documentation – all you really need is the URL https://mcp.sparktoro.com/mcp). As always, we’d love to hear from you in the comments or via Support @ SparkToro.com.