Apollo Chrome Extension vs API: Get the Same Data Without a Browser

Get what the Apollo sidebar shows for a company and its people, without opening a browser. Paste this into your agent:

Set up https://monid.ai/SKILL.md, and then use Monid to enrich patagonia.com with Apollo, then list the VPs and directors there with Apollo's free people search and tell me how many have an email on file.

One prompt does the sidebar's job. 1 min setup · 15-30 hrs saved.

You use the Apollo extension to look at one company at a time, and now you have a list of fifty or four hundred, or a sequence that should enrich every new lead on its own. A sidebar cannot loop, so the question is which of its jobs an API call can take over. This guide maps each sidebar action to a call, shows what one company call and one people search returned when we ran them on 2026-10-16, and lists what changes when a program does the looking. It runs through Monid, the OpenRouter for agent tools: one key, one balance, every tool priced per call.

What is the easiest way to get Apollo data without the Chrome extension?

Monid. Install it once, add a key, and your agent calls Apollo's company enrichment, people search and people match with no browser tab, no seat and no Apollo portal to set up.

• Pay per call. A company enrichment costs $0.026 and a people match costs $0.026 (Verified 2026-10-16 on the Apollo tools page). The people search that builds the list is free. Buy calls as you need them: no monthly plan and no minimum top-up. Discovery and inspection are free; only a run bills.
• One install, every API. The same key and the same balance call Apollo and every other tool on Monid, so the next data source is one more command, not one more account. Wiring those yourself is the 15 to 30 hours this page claims to save.
• Lives inside your agent. Install the CLI, add your key, run the prompt above, and the tools are there whenever your agent needs them, with nothing to keep running. Your agent reads SKILL.md and learns the rest, so setup is about a minute.

For a list of 200 company domains, the enrichment pass is 200 calls, $5.20 (Verified 2026-10-16).

What does the Apollo extension do, and which API call does the same job?

The extension reads the page you are on and shows Apollo's record for it in a side panel, and each thing the panel shows has a call behind it. The difference is not the data. It is who drives: the sidebar follows your navigation, a call follows your list.

The prices were read with monid inspect on 2026-10-16. The phone row is the mobile tier of the match endpoint, and the flag alone never charges: the extra charge applies only when a number comes back.

Where the sidebar wins and where the call wins

The sidebar wins on context. You see the record next to the page that made you curious, and you decide in a second whether it is worth a click.

The call wins on repetition. A call takes an identifier and returns a record, so a list of domains is a loop, a schedule or a trigger on a new CRM row. Nothing about a browser panel can do that unattended.

The call also returns more than fits in a panel. One company call came back with 66 fields on the organization, which is a record, not a sidebar. The measured section below shows what is in it.

If your task is to turn a title search into a full lead list, exporting Apollo leads by API walks through that pattern end to end.

How do you replace the extension with API calls?

Enrich the company first, search people for free, then reveal only the rows you will use. That order keeps the bill small, because the cheap steps remove most of the list before the paid step runs.

For agents

Grab an API key at app.monid.ai, then paste this to your agent and hand it the key:

set up https://monid.ai/SKILL.md

It learns the whole discover, inspect, run workflow itself. More in the agent quickstart.

For humans

npm install -g @monid-ai/cli
monid keys add -k <your-api-key> -l main

Step 1. Enrich the company

monid run -p apollo -e /organizations/enrich --query '{"domain": "patagonia.com"}'

The input takes one of domain, linkedin_url, name or website; more identifiers improve the match, and a company Apollo cannot match consumes nothing. On 2026-10-16 this call took about 1.3 seconds and returned the organization with 66 keys.

Step 2. Search the people, free

monid run -p apollo -e /mixed_people/api_search \
  --query '{"q_organization_domains_list[]":["patagonia.com"],"person_seniorities[]":["vp","director"],"per_page":3}'

This returned 3 rows out of a total_entries of 132 at no cost, in about a second. Each row has an Apollo id, a first_name, the last name masked, a title and flags such as has_email. The flag says an email exists; it does not hand it over. Run monid inspect -p apollo -e /mixed_people/api_search before you copy filter names from anywhere else: the endpoint declares its own list, including person_titles[], organization_num_employees_ranges[] and technology filters.

Step 3. Reveal the people you chose

monid run -p apollo -e /people/match \
  --query '{"first_name":"Jane","last_name":"Doe","domain":"patagonia.com"}'

Match takes any mix of first_name, last_name, name, email, domain, organization_name, linkedin_url and the id from step 2. Leave both reveal flags off for a plain work email. Set reveal_personal_emails only when you will write to a personal address, and reveal_phone_number only when somebody will dial, because that run is asynchronous and stays running for several minutes.

For one name in and one email out, the Apollo email finder guide goes deeper on the match call and what its status fields mean.

Can you automate the extension itself?

You can, but you would be scripting a browser to click a panel, and that breaks whenever the page or the panel changes. A scraper of the sidebar needs a logged-in browser session, a way to survive layout changes and a pace that looks like a person, and its output is whatever the panel chose to render. The call returns the record itself, as JSON, with the same fields every time.

Rules differ by site and by plan. LinkedIn, Apollo and your own employer each have terms on automated access to a logged-in session, so read the ones that apply to you before you build anything that drives a browser at scale.

What Monid maintains for you is the part that goes stale: the endpoint, its input schema, its price and its status. Your agent runs monid inspect before each call, so a changed parameter shows up as a schema, not as a broken script at 2 a.m.

What does the API return that the sidebar does not?

A full organization record, 66 fields in one call, and a search response designed for lists. Both are measured on 2026-10-16.

The company record

The call for patagonia.com returned, among its 66 keys:

estimated_num_employees   4000
annual_revenue            1470000000   (printed "1.5B")
founded_year              1973
industry                  "retail"
retail_location_count     75
total_funding             null
funding_events            []
num_suborganizations      6
keywords                  120 entries
technology_names          286 entries
departmental_head_count   19 departments, e.g. sales 274, marketing 195, engineering 120

Three layers are worth knowing. Firmographics (headcount, revenue, founding year, address, industry, phone) are what a sidebar summarises. Structure (six suborganizations, a department-by-department headcount, six, twelve and twenty-four month growth rates) is what you filter and sort a list on. Positioning (120 keywords and a written description) is what you hand to a model to draft a first line. The funding fields came back empty, which is the right answer for a company that has raised nothing Apollo tracks.

The people search

Each of the three rows carried has_email true and has_direct_phone "Yes", a title, a refresh timestamp and the masked last name, with no address or number. That is the point of the shape: you can size and filter a population for nothing, then pay to reveal only the rows you will contact.

What you can build with it

A scored account list. Enrich every domain, keep headcount above your floor, and rank by the department you sell into. A sidebar gives you one such number at a time; a call gives you a column.

A coverage check before you buy. Search each account for the buyer title and count the rows with has_email true. An account with no reachable buyer drops out before it costs a match.

A trigger. When a new lead lands in your CRM, enrich the company and write the headcount and industry back. Enrichment as a step in a pipeline, not a lookup, is the pattern in sales automation by the call.

What goes wrong when a program replaces the sidebar?

Four things surface only once a loop does the reading. The first two come from the company record and the search we ran on 2026-10-16.

Why does the technology list contain repeats and one-word entries?

Because it accumulates every technology ever detected on the domain, so it is evidence of presence, not a current stack. In the Patagonia record, technology_names held 286 entries but only 267 distinct names, and 17 names appeared more than once: MailChimp three times, Microsoft 365 three times, AngularJS, Bootstrap and Zendesk Chat twice each. Members included AI, Air, Adobe, Gem, Hive, Snap and CAT, which a stack cannot contain as products.

Deduplicate, then filter for specific names. Keep a technology only when it is a named product. Treat "Salesforce is in the list" as a weak positive (15 entries mentioned it here) and treat "Segment is not in the list" as no information. Verify the one technology your outreach depends on with a live detector, as the technographic data guide shows.

Why do headcount and revenue disagree with each other?

Because they are modelled estimates. The same record gave estimated_num_employees 4000 while its own written description said the company employs around 3,000 people. Use these numbers to sort and to segment, where the right order of magnitude is enough, and never quote them as figures.

Why is a search row not a contact?

Because search is built to withhold the contact. The row has the flag, not the address, and the last name is masked, so the id is what you carry into the match call. Skipping the search and matching a guessed name wastes calls.

Why can a match bill when it returns nothing useful?

Because the base charge applies when Apollo can attach the name to a known company, even if the person comes back with no email and no title. Monid's pricing note for the endpoint says so, and an earlier match we ran on a low-confidence name returned a null title and a null email and billed the base. A match that finds no company consumes nothing. The defence is to match from the id of a search row that showed has_email true, not from a name you typed.

Which endpoint should I use for which job?

Current figures are on monid.ai/tools. We ran the first two rows on 2026-10-16 and inspected the other two. Use the companies search to build the account list, enrichment to qualify each account, people search to find the buyer for free, and match only for the people you will contact. How the per-contact tiers of a sibling vendor compare is laid out in the RocketReach per-contact pricing guide.

When is the extension the better fit?

A person is doing the research. If someone is reading a company page and wants the contacts beside it, the sidebar is the right interface and no API makes that faster.

Your volume is a handful a day. Below a few dozen lookups, an integration costs more to write and keep than the clicking does.

You want the workflow, not the data. Sequences, task queues, CRM writeback and team sharing are product features around the sidebar. Per-call endpoints deliver records, and none of that.

You need your own CRM records enriched inside Apollo. Saved searches, alerts and seat features belong to the product. A call gives you fields to put in your own system.

And the disclosure: we resell these endpoints. The advice that costs us calls is to enrich first, search for free and match from an id that showed an email on file, which together buy you fewer paid lookups than a person clicking through.

Conclusion

The quickest way to get what the Apollo sidebar shows, without the browser, is a company enrichment, a free people search and a targeted match through Monid: $0.026 for the company and $0.026 for each match (Verified 2026-10-16), one key for Apollo and everything else, about a minute to set up and ready inside your agent whenever you need it. The extension stays the better tool for one company read by one person.

Two things matter more than the choice. Read the technology list as presence evidence only, because a list of 286 entries with 17 repeated names is an accumulation, not a stack. And treat headcount and revenue as bands: the same record gave 4,000 employees in a field and about 3,000 in its own description.

How we estimated the time saved: building an enrichment call, a paged people search with filters, and a match step with async polling is roughly 5 to 10 hours each, 15 to 30 hours in all. The 1 minute is the install, key and first call once you already have a Monid key.

Free next step: run monid inspect -p apollo -e /organizations/enrich, enrich one domain you know well, and compare the headcount and technology fields with what you expect. Start at monid.ai.

FAQ

Published September 2026.