Glasser

Best companion of agents providing pay-as-you-call premium data.
One line setup with your AI Agents.
All in one key - no subscriptions, no minimums.

[Glasser @Glasserai]

The BEST prompt in the universe:

set up https://t.co/x1CoABptm0

Send it to your agent. It finds and calls the right tools through Glasser, then gets live data straight from the source.

No subscriptions. Pay per call.

[Glasser @Glasserai]

Glad to make this happen together with @adalagent @PromptQL @n8n_io @snyksec @RocketRideAI @tenki @FinchTechAI @prelint_ai @band_hq @kylon_ai @CelestoAI @AskTheWHQ @awscloud !!!

[Glasser @Glasserai]

Spent a whole day at AWS Builder Loft with a room full of builders creating their own AI workforce!

Glasser gives agents one key to 2,000+ data tools and APIs. Pay per call, no subscriptions.

[Glasser @Glasserai]

@SDoshi1108 sad, this link doesn't work

[Glasser @Glasserai]

Share an amazing hackathon project: Competitor ad research, minus the scrolling. Each Meta or LinkedIn ad library pull in 「Helios」 runs through Glasser at about $0.00188 a call!!

[Shruti Doshi @SDoshi1108]

Still manually scrolling through Meta & LinkedIn ad libraries to see what your competitors are testing?
I built Helios, an automated Competitor Ad & Messaging Tracker that catches your competitors positioning shifts using https://t.co/tJHpF82G8R @adalagent & Jev.

[Glasser @Glasserai]

Hey @shengkunye, @feiyou_guo just followed us.
Is @MonidHQ about to kill us?

[Glasser @Glasserai]

@Mortezabihzadeh yes, agents need better data to eat.

[Glasser @Glasserai]

Imagine spending a fortune on the smartest AI model, then asking it to build your GTM strategy from three outdated blog posts.

Yeah. That's the problem we're trying to solve.

Appreciate the write-up! 🧡

[Morteza @Mortezabihzadeh]

Your AI agent can write code, plan a launch and answer emails...

But ask it one real business question and it goes digging through the open web

Old blog posts, half true numbers, pages written by another AI. Then it builds your answer on top of that

The model is fine. The data is the weak part

If you build with agents you know this pain. We keep upgrading models and prompts while the agent still eats junk data

Glasser fixes exactly that

It's a data layer for AI agents → one key, one balance, 1,700+ endpoints from providers like Ahrefs, Apollo, Semrush and ZoomInfo. Your agent pulls premium data the moment it needs it

Here is what that looks like in real work:

→ Lead lists from your ideal customer profile, filled in from just a name or an email
→ Company research before a sales call: size, industry, recent news
→ Which keywords your competitors are winning
→ Brand mentions tracked in the news every hour
→ Price comparisons for a product across stores

Look at the lead flow in the image:

You type a company domain → Glasser finds the CTOs and engineering leaders → the AI picks one → Glasser finds the work email → you get a lead card with sources, ready to review

No scraping, no exporting spreadsheets, no copy pasting into chat

Now the part I like most as a builder

Setup is one line. You paste this into your agent's chat:

set up https://t.co/mg3zttLNiN

The agent installs it and signs in by itself. You approve once in the browser and your key never passes through the chat. Thats a big deal if you care about security

The pricing makes sense for small teams too. Glasser is pay per call and you see the price of each call before it runs. No contract, no monthly bill for 10 data tools you open twice a month

You also get $1 free credit when you sign up, no credit card needed

And it works with Claude, Codex, Cursor, Grok and more. Same agent, same workflow, way better data

Try it in 3 steps:

Open https://t.co/0H2LATPn8l
Tell your agent: set up https://t.co/mg3zttLNiN
Ask for the data you need

Give your agent real data and watch how much smarter it gets

What would you ask your agent first? 👀

#GlasserAI

[Glasser @Glasserai]

AI made building ridiculously easy.

Figuring out what's actually worth building? Still hard.

Love this experiment. Instead of spending a weekend shipping another SaaS, he spent $0.008 on real search data to see what was already out there.

More builders should do this before writing code.

[Jahir Sheikh @jahirsheikh8]

https://t.co/MGd1LUsm34

[Glasser @Glasserai]

@jahirsheikh8 This is exactly the kind of experiment we love seeing. $0.008 to ask better questions before writing a line of code. Appreciate you sharing the whole process, including what didn't work! 🧡

[Glasser @Glasserai]

@babayagatwt great article! just brought Grok + Glasser to the next level.

[Glasser @Glasserai]

Most affiliate "lead lists" are just strangers with email addresses. This one finds people actually asking for help. Turning @grok into an Affiliate Lead Finder is insane, and very much worth a try. Grok + Glasser = wild🔥

[baba yaga @babayagatwt]

Finding genuine affiliate leads on the raw web is harder than it looks.

I got tired of that, so I built a Glasser workflow that actually finds people asking for help and I put it all in this article. https://t.co/8E6AoMqiBI

[Glasser @Glasserai]

@Mortezabihzadeh One prompt, connect your agent to premium data: set up https://t.co/J6ep0r4gFo 😎

[Glasser @Glasserai]

@celineycn 🤓

[Glasser @Glasserai]

https://t.co/m9BMr4K64A

[Glasser @Glasserai]

@shedntcare_ nailed it😌

[Glasser @Glasserai]

This is incredible. Our user built an @n8n_io workflow that researches their whole target list every morning.

Glasser pulls each company's profile, tech stack, news and funding. Claude scores the fit. Top accounts get verified contacts and a Gmail draft.

https://t.co/wNmtXdlpOd

[Glasser @Glasserai]

secret sauce when facing investors!

[Glasser @Glasserai]

We had agent + Glasser check what top VC partners post on X against the AI deals their firms led in 2026.

Most theses were public weeks or months before the money.

Here's how AI builders can use that before the next pitch. https://t.co/T5A6aUPnxQ

[Glasser @Glasserai]

We had agent + Glasser check what top VC partners post on X against the AI deals their firms led in 2026.

Most theses were public weeks or months before the money.

Here's how AI builders can use that before the next pitch. https://t.co/T5A6aUPnxQ

[Glasser @Glasserai]

@jahirsheikh8 thank you!

[Glasser @Glasserai]

We turned AI agent into a corporate spy target Duolingo.
It investigated 110 Google ads, 22 Meta ads, and 3 competitors.
We broke down its strategies into 4 growth tactics you can steal for your own product.
Here's what we uncovered 👇 https://t.co/AjxbkiBQ9Q