As with any AI tool, it's important to keep in mind what an MCP excels at as well as where it may be prone to missteps. To help guide your work with the Dscout MCP, we've compiled a list of best practices for you to follow:
Ground with context
Start your chats by offering context about your research. Describe what your goals are or what you're hoping to learn. This can help kickstart your conversation with the AI, and it'll be able to offer you guidance if you get stuck or aren't sure what to look into next.
Break complex work into chunks
Sending one long prompt with multiple requests gives AI more chances to head in a direction other than what you intended. Instead, break your requests into logical chunks. This will give your conversation and workflow natural checkpoints for you to keep an eye on what's being done. Don't put all your eggs in one basket (at least not one held by a robot).
Be specific when possible
Don't let the AI guess. If you're looking for data from a specific study, clearly state that study's title, preferably in its full form. Abbreviations can often be misinterpreted, especially if you've got a few Dscout studies or projects with similar names.
When drafting, tell the tool what you want it to do with as much detail as possible. Adding a question? Tell it where you want the question to be placed in the study, any wording preferences you might have, and anything else that's relevant to your specific request.
Check your settings
There are some question-level settings the Dscout MCP can't adjust. For example, Close task URL on Task questions must be set manually. We recommend double-checking these settings in the Dscout UI prior to launch.
Start broad before homing in
When querying your data, start broad to ensure you and your AI tool are on the same page. For example, prompt the AI to locate the study or studies you want to analyze. Once you've confirmed it's looking at the correct data, then ask more specific questions.
Always fact check
Any AI tool can hallucinate or misinterpret your requests—and they'll often do it with confidence. So, we recommend occasionally verifying the AI's sources. If it's giving you participant quotes, pop into your study to verify they're accurate and not being taken out of context.
Preview before launching
After the MCP creates or modifies a study, open it in Dscout and review it yourself before going live. Check that questions read the way you intended, recruitment criteria and incentives are correct, and nothing was skipped or misinterpreted.
Let us know what feels off
If you run into something that doesn't feel quite right, we want to know! Reach out to support@dscout.com so we can help and make any improvements where possible.