Prepare your next client review with Instagram profile and post data in ChatGPT or Claude. Connect Instagram Public Data through Catchr, select the relevant accounts, and use Catchr MCP to ask about followers, post likes, comments and publishing patterns.
For freelancers and agencies, it is a practical way to turn connected Instagram data into focused questions and useful reporting summaries.
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Instagram Public Data
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Build your analysis around profile counts, media likes and comments, and the captions and hashtags attached to posts. Use publication dates to keep post reviews within the client reporting period.
Review Profile Followers, Profile Follows and Profile Post Count alongside the account name, username, biography and website. Use these details to prepare a profile overview or check which account a client report covers.
Keep profile counts separate from period-based post analysis: a follower count alone does not establish follower growth over time.
Compare Media Likes and Comments for posts published during your selected date range. Read Post Caption and Post Hashtags alongside those counts to identify content worth reviewing in a client meeting.
Use Post Caption Length (without Hashtags) and Post Hashtag Count to compare content patterns. Treat differences in likes and comments as observations, rather than proof that a caption length or hashtag choice caused the result.
Group media by publication day, week or month to organize a client content review. Day of the week and hour of the day also let you compare posts published at different times.
The selected media date window includes both boundary dates. Likes and comments associated with those posts should not be described as interactions that necessarily occurred within that window.
A focused Instagram analysis, a prepared client report and a question through Catchr MCP serve different needs. Choose the approach that fits whether you are investigating posts, presenting results or answering a follow-up question.
Use a report to give clients a consistent Instagram overview. Use Catchr MCP when you need a focused follow-up, such as which posts drew the most comments or how likes varied across hashtag-count groups.
Connect Instagram Public Data in Catchr using OAuth authorization and select the relevant accounts. Then connect ChatGPT or Claude through Catchr MCP. Start with a profile overview, or specify a publication date range to ask about post likes, comments, captions and hashtags.
Replace the bracketed values with your account selection, reporting dates and thresholds. Each prompt gives you a concrete starting point for reviewing Instagram Public Data.
Using Catchr, prepare an Instagram Public Data profile overview for [accounts]. Show each account's name, username, biography, website, Profile Followers, Profile Follows and Profile Post Count. Flag missing biography or website values, and keep this overview separate from any claims about follower growth.
Copy promptUsing Catchr, review posts for [account] published from [start date] through [end date], inclusive. Keep posts with at least [minimum comments] Comments and rank them by Comments, then Media Likes. Show publication date, Post Caption, Post Hashtags, Comments and Media Likes. Summarize recurring caption topics in the shortlist without claiming they caused the results.
Copy promptUsing Catchr, analyze posts for [account] published from [start date] through [end date], inclusive. Group them into posts with no hashtags, one to [hashtag threshold] hashtags, and more than [hashtag threshold] hashtags. For each group, calculate the number of returned posts, average Media Likes and average Comments. Include example captions and hashtags, and flag groups with fewer than [minimum posts] posts before interpreting differences.
Copy promptUsing Catchr, compare posts for [account] published from [start date] through [end date], inclusive, by day of the week. Calculate the number of returned posts, average Media Likes and average Comments for each day. Flag days with fewer than [minimum posts] posts and identify patterns worth testing in the next content plan. Explain that these are results grouped by publication day, not the day each interaction occurred.
Copy promptYou can ask about profile followers, follows and post count, plus account details such as username, biography and website. For posts, you can analyze likes, comments, captions, hashtags, caption length without hashtags and hashtag count.
Connect Instagram Public Data in Catchr through OAuth authorization, select the relevant accounts, and connect your AI destination through Catchr MCP. Include the account and publication dates in post-analysis questions so the requested scope is clear.
The date range selects posts by their publication timestamp, including the start and end dates. You can group those posts by date, week, month, day of the week or hour. Their likes and comments do not establish when individual interactions happened.
Profile Followers provides a follower count; it does not establish historical growth on its own. Media Likes and Comments support post comparisons, but reach and impressions are not included in this field set, so reach-based or impression-based engagement rates cannot be calculated from it.
Connect your sources to Catchr, add the MCP server to your AI assistant, and ask about the work that matters now.
