TL;DR: AI analytics for social media posts sounds like one feature, but each platform gates it differently. LinkedIn’s Member Post Analytics API is free to use but limited to a short list of approved vendors, X charges per read, Dev.to’s stats endpoint is free and open to any account, and Reddit’s post insights have no public API at all.
You published to LinkedIn, X, Dev.to, and Reddit this week: four platforms, four dashboards, four separate login screens. Now you want one plain answer: which post actually pulled its weight? Ask LinkedIn and you need to be one of 11 approved vendors or you’re stuck reading its native app. Ask X and it’s $0.005 a read against a 2-million-read monthly cap. Ask Dev.to and it’s a free API call that refreshes once a day. Ask Reddit and there’s no API at all, just a chart under “See More Insights” on the post itself.
Why “just pull the analytics” turns into a per-platform negotiation
The pitch behind most “AI social media analytics” tools is that performance data is one API call away, the same way posting is. It isn’t. Every platform decided independently who gets to read a creator’s own numbers, and the four answers above land nowhere near each other: an approval list, a metered price, a free public endpoint, and a UI-only chart with no documented way in. An AI agent that’s supposed to tell you “what worked” has to clear whichever of those gates applies before it can compare anything.
That’s a different problem from posting. Publishing usually has one blocker: does the platform give out write access at all. Reading your own performance data has the same blocker plus a second one: even where an API exists, is it priced or gated in a way an individual creator can actually use.
What each platform actually lets you pull
| Platform | Who can get your own post data | Cost / access model | What you actually get |
|---|---|---|---|
| Only through 11 named approved vendors | Free to those vendors, application-gated for anyone else | Follower growth, post impressions, video views | |
| X (Twitter) | Any registered developer | $0.005 per post read, $0.001 for reads of your own account’s data, 2M reads/month cap | Impressions and engagement metrics tied to the post |
| Dev.to | Any account holder with an API key | Free, no approval process, updates once a day | Page views, reactions, comment counts per article |
| Nobody, via a documented API | No confirmed public endpoint; data only shows in the UI | Upvotes, a views-per-hour graph, shares, awards | |
| Medium | Nobody | API closed to new integrations since 2023 | None via API |
Bottom line: Dev.to is the one platform here that just hands you your own numbers for free. Everything else adds a cost, an approval process, or simply doesn’t offer a documented way to read it, which is why “connect everything and let AI compare” is a harder promise to keep than it sounds.
Why LinkedIn opening this up in 2025 actually mattered
For years, LinkedIn creators had no way to see post performance anywhere but LinkedIn’s own app. That changed on July 8, 2025, when LinkedIn launched its Member Post Analytics API, exposing follower growth, post impressions, and video views for a member’s own content. Sam Corrao Clanon, LinkedIn’s director of creator products, told Digiday the goal was to “make the value of LinkedIn as accessible as possible for people who are contributing their knowledge,” giving creators a fuller picture of their reach without forcing them to live inside LinkedIn’s dashboard.
The catch is access. Third-party vendors don’t pay LinkedIn anything for the API, but they do need to apply and be approved, and as of this API’s launch only 11 tools had that approval: Hootsuite, Buffer, Sprinklr, Metricool, Oktopost, Zoho, mLabs, SocialPilot, Later, Publer, and Vista Social. If your workflow isn’t built on one of those, LinkedIn’s own numbers still mean opening the app.
What reading your own session gets you that an API doesn’t
This is where PublishPort’s model works differently from an API integration. Instead of registering an app and waiting on LinkedIn, Dev.to, or Medium to approve it, the client runs on your machine and reads whatever’s already visible in the browser session you’re logged into. An AI agent gets two tools to work with: list_capabilities(), which lists what’s available per platform, and local_bash(cmd), which runs the read through PublishPort’s ppcli CLI against that same logged-in session, the same model we covered in how MCP servers for publishing actually work. There’s no vendor application to file and no per-call bill, because nothing is calling LinkedIn’s or Dev.to’s API at all.
That only covers what’s on the page today, though. It’s LinkedIn, Medium, and Dev.to right now, where a creator’s stats already render in their own dashboard. X and Reddit aren’t part of that yet, so an AI running through PublishPort can publish to and engage with both (see how AI auto-reply works, and where it doesn’t, on each platform) without yet pulling their performance numbers the same way. If your review workflow depends on X or Reddit metrics specifically, that piece still means the platform’s own path: X’s metered API or Reddit’s in-app chart. PublishPort closes the gap for the platforms where it exists; it doesn’t invent access nobody has.
Wiring this into an actual review habit
The useful version of “AI analytics” isn’t a live dashboard, it’s a standing check. Point an agent at your logged-in LinkedIn, Dev.to, and Medium sessions once a week and ask it to pull last week’s numbers, flag the post that outperformed the rest, and note anything that fell flat. That’s a five-minute read instead of opening three separate dashboards and doing the comparison by hand. It’s also the other half of a full content loop: write once, publish everywhere, catch replies as they come in, then close the loop by seeing what actually landed before you write the next one.
A standing review that holds up: pull last week’s post impressions and reactions from every platform where you have access, rank them by engagement rate rather than raw views (a 200-view post with 40 reactions beat a 2,000-view post with 5 in every review we ran this way), and use whichever post won as the template for tone and length next time. That comparison only works with numbers you can actually get, which is exactly the platform-by-platform reality above.
Limits worth stating plainly
- This isn’t a unified dashboard. Reading a browser session is platform-by-platform, and a couple of the platforms creators care about most, X and Reddit, aren’t covered through this route today.
- A logged-in session reads what’s rendered, not a stable contract. Where a platform changes its own dashboard layout, that reading breaks until it’s updated, unlike a versioned API with a deprecation notice.
- None of this changes what LinkedIn, X, or anyone else charges or gates for their own API. If you need X’s numbers through X’s own API, its per-read pricing still applies regardless of how you publish.
- Numbers are a snapshot. LinkedIn’s vendor list, X’s pricing, and Dev.to’s refresh cadence are all things that change; check the source pages linked above before building a workflow that depends on them staying exactly as described here.
Before you build a review workflow around this
- Confirm which platforms you actually need numbers from, not just which ones you post to.
- Check whether your existing tools are on LinkedIn’s approved vendor list before assuming you already have access.
- Budget for X’s per-read cost if programmatic X analytics matter to you; it isn’t optional or free.
- Treat Dev.to’s daily refresh as the baseline for “real-time,” not a limitation to work around.
- Re-verify access models before scaling a workflow past a handful of platforms; the ground here shifts often.
FAQ
Does LinkedIn have an API for post analytics?
Yes. LinkedIn’s Member Post Analytics API launched July 8, 2025, exposing follower growth, post impressions, and video views for a member’s own content. It isn’t open to any developer who registers, though: access currently runs through 11 approved third-party tools, including Hootsuite, Buffer, Metricool, Later, and Publer, with LinkedIn saying more integrations are planned.
How much does the X API cost for reading post analytics?
Since February 2026, X has run on pay-per-use pricing with no free tier: reading a post’s data costs $0.005 per read, capped at 2 million reads a month before Enterprise pricing kicks in. Reading your own account’s own data through “owned reads” is cheaper, at $0.001 per resource.
Can I get analytics for my own Dev.to articles for free?
Yes. Dev.to’s authenticated /api/articles/me endpoint returns page view counts, reaction counts, and comment counts for your own posts at no cost and without an approval process, though the numbers only refresh once a day.
Does Reddit show how a post is performing?
Reddit’s own “Post Insights” panel, visible under “See More Insights” beneath a post you made, shows upvotes, a views-per-hour graph for the first 24 hours, shares, and awards. There’s no confirmed public API for pulling that same data programmatically, so anything reading it today is reading the page, not a documented endpoint.
Can AI automatically tell me which of my posts performed best across platforms?
It can compare numbers once it has them, but getting those numbers from LinkedIn, X, Dev.to, and Reddit means clearing four different access models first: application-gated, pay-per-read, open and free, and no API at all. “Automatic” still depends on what each platform is willing to hand over.
Is there a single API that covers analytics for every social platform?
Unified providers like Ayrshare and Data365 bundle several platforms behind one API key, trading per-platform integration work for a subscription fee and whatever coverage gaps the provider has, including platforms like Medium that don’t expose analytics through any API. It’s a real option, just not a free one.