For GTM engineers
68 data endpoints behind one key, over REST and MCP. The three waterfall endpoints, email_finder, phone_finder and email_verifier, return an execution_log on every call: which providers ran and why each one missed.
We don't publish match rates. Run a list you already know the answers for, and count.
Workflow
Prototype the workflow in a spreadsheet or a Clay table. When it's settled, move it to a script or an n8n flow: the same endpoints, one key, a schedule.
Every endpoint's credit rate is in the OpenAPI spec, so you can price a job before you run it.
for row in leads: email_finder(row)
Signals
Some endpoints read live data at request time. These are the signals: things people and companies did this week, not a record last refreshed months ago.
Read live at request time:
Pricing
No seats: you pay for credits used, not for users. Search endpoints bill per result, so asking people_search for 100 people and getting 73 bills 73 profiles.
On the waterfall endpoints, a lookup that returns no result bills zero.
people_search · 0.1 credit per result
= 7.3 credits
Run a fair test
email_finder without the emails.execution_logon the ones that didn't.FAQ
"billed": false. A call that returns a result bills at the published rate, so a wrong result still bills, and so does an "invalid" verdict from email_verifier. That's why step 3 of the test matters.mcp.richapi.ai/mcp. Credits come from the same balance.