Same scrape, then scored
Zevari pulls the likers and commenters off any post too - then runs each one through ICP scoring 1-5 with a written reason per person. You read the 1s and 2s out and work the 4s and 5s. The list arrives ranked, not raw.
Goji Berry scrapes the people who liked and commented on a viral post into a clean list. That is genuinely useful - and it is where Goji Berry stops. Zevari does that same scrape, then scores every name 1-5 against your ICP with a reason for each, drafts the outreach in your voice, and runs the campaign with every send staged for your approval. A list is not pipeline.
The one-line version
Hands you a spreadsheet of post engagers. It built the haystack. Reading each profile, judging fit, writing something that does not sound like a bot, sending it without tripping LinkedIn's limits, then chasing replies - that is still entirely on you.
Hands you a ranked, reasoned target list - and then does the outreach for you. It finds the needle, tells you why it is the needle, and reaches out, with every send under an approval gate.
Where Goji Berry is good
Goji Berry does one job well: it scrapes the likers and commenters off a LinkedIn post and gives you a clean export. If a competitor or a thought leader drops a post your exact buyer engaged with, that engagement is a real intent signal, and Goji Berry captures it fast. As a Chrome extension it is cheap and quick, and for "I just want the list" it does the thing.
If all you need is the raw list and you will handle scoring and outreach yourself, Goji Berry is a reasonable tool. We are not going to pretend otherwise.
Where the list runs out
You now have 300 names in a spreadsheet, and most LinkedIn posts pull a messy crowd: a few real buyers, a pile of peers, some job-seekers, a couple of competitors, and the people who like everything.
"finding that needle in a haystack... it's really hard to do."
That work - judging fit, writing the message, sending it safely, chasing the reply - is the part that eats the day. That is the part nobody wants to do.
The scoring gap
A scraper gives you the haystack. It does not find the needle. Zevari pulls the same engagers, then turns the raw list into a ranked, reasoned target list before you ever open a profile.
Zevari pulls the likers and commenters off any post too - then runs each one through ICP scoring 1-5 with a written reason per person. You read the 1s and 2s out and work the 4s and 5s. The list arrives ranked, not raw.
Beyond a single post, Zevari finds people who posted in the last 30 days about your topic - live intent, not a static export that is stale by the time you open it.
Hand it one customer or a single profile URL and it finds more like them, scored against your ICP. No filter-stacking, no manual reading of 300 profiles.
The execution gap
A scraper has no opinion on what you say next, no way to warm a prospect, and no memory of who replied. Zevari is the brain and the hands - reachable over MCP for Claude Code and Codex, or our REST API from your own code.
Drafts trained on your sent messages, so the outreach sounds like you, not like AI. A scraper has no opinion on what you say next; Zevari writes the next message.
Comments, reactions, and profile views before the ask, so you are not a cold stranger sliding into a DM.
Multi-step LinkedIn campaigns - warm actions, connection note, follow-ups - built and advanced by your agent, not by you pasting into a DM box 300 times.
When replies come in, they are classified by intent and a draft response is staged for your approval. The list never told you a reply came in. Zevari does.
And because Zevari holds hosted state, the warm-up runs today, the connect tomorrow, the follow-up Friday - persistent scheduling a Chrome extension, and even Claude Code or Codex alone, cannot hold.
Where it lives
Goji Berry is a Chrome extension you click through one post at a time. Zevari is a hosted MCP server your agent connects to - 60+ tools for search, signals, scoring, campaigns, inbox, and content. Reach Zevari over MCP for Claude Code and Codex, or our REST API from your own code.
claude mcp add zevari https://mcp.zevari.ai/mcpSafety
Browser-extension scrapers operate in your logged-in session and lean on what LinkedIn can see in the browser. Zevari connects session-based with no browser cookies, and every write action is staged for your approval before it fires. A year of refinement, zero ban incidents. Receipts, not adjectives.
Read the full safety modelThe honest table
Goji Berry is a scraper; Zevari is the brain and the hands. Here is the straight version.
Yes
Yes
No
Yes
No
Yes, signal-based targeting
No
Yes, Voice DNA trained on your sent messages
No
Yes, built and advanced by your agent
No
Yes, Inbox Radar
No
Yes, warm-by-default
No, manual export
Yes, persistent hosted state
Not applicable, no sending
Yes, approval gates on every write
Logged-in browser session and cookies
Session-based, no browser cookies
Not applicable
Yes, Free 40 / Premium 80 / Sales Navigator 150 per week
No
Yes, hosted LinkedIn MCP plus REST API
No
Yes, Managed and done-for-you
Chrome extension
MCP execution layer for Claude Code or Codex
Run both, then decide: you do not have to rip anything out on day one. Plenty of people keep Goji Berry as one input - grab a list off a hot post - and pipe those names into Zevari to be scored, written, and worked. Many teams start by augmenting, then realize Zevari's own scrape plus scoring plus outreach makes the separate extension a step they no longer open.
FAQ
Zevari. Goji Berry scrapes LinkedIn post likers and commenters into a list and stops there. Zevari runs the same scrape, then scores every prospect 1-5 against your ICP with a written reason for each, drafts outreach in your voice, and runs the campaign with every send staged for your approval. You get a ranked, reasoned list that gets worked - not a raw spreadsheet.
Yes. Beyond scraping a single post's engagers, Zevari's signal-based targeting finds people who posted about your topic in the last 30 days - live intent, not a static list - scores them against your ICP, and can run the outreach for you with approval gates on every send.
Each prospect gets a 1-5 score with a written reason (for example, 4/5 - VP of Sales at a 50-person B2B SaaS, posted about pipeline gaps last week). You read the low scores out and work the high scores. You can also correct it - tell it when someone is not your ICP and it learns.
It runs the outreach - warm-up actions, connection notes, multi-step sequences, and reply handling - but every write action (message, connection, comment, post) is staged for your approval before it sends. You approve from chat or Slack. Nothing touches your account without your sign-off.
Goji Berry runs in your logged-in browser session as a Chrome extension. Zevari connects session-based with no browser cookies, stages every write for human approval, and enforces weekly connection ceilings (Free 40, Premium 80, Sales Navigator 150), working hours, behavioral pacing, duplicate checks, and burst caps. A year of refinement, zero ban incidents. Full mechanics are on the safety page.
No. Many teams keep Goji Berry as a list input and pipe those names into Zevari to be scored, written, and worked. Goji Berry is a scraper; Zevari is the execution layer. Most people find Zevari's own scrape plus scoring plus outreach replaces the separate extension over time, but you can run both.
No. Engineers run it as outbound-as-code: reach Zevari over MCP for Claude Code and Codex, or our REST API from your own code. Non-technical founders and agency owners use the Managed option - we set up and run the engine on our infrastructure and you approve sends from Slack in minutes a day.
Same approval-gated engine on both lanes. Reach Zevari over MCP for Claude Code and Codex, or our REST API from your own code.
You are a GTM engineer who wants outbound-as-code: a scored target list, voice-matched drafts, campaigns advanced on a schedule, all with every send under an approval gate. Connect over MCP for Claude Code and Codex, or call our REST API from your own code.
Connect to Claude CodeYou are a founder or agency owner who just wants fewer hours in the DMs and more booked calls. If you are already paying an appointment setter or AI SDR, we run the same engine and you approve every send from Slack in minutes a day.
We run it for youZevari - the LinkedIn execution layer for Claude. Your agent sleeps; your pipeline doesn't.