ApexVerify

@ApexVerify check my account credits and show me the status of any batches created in the last 7 days

Your ApexVerify account currently holds 12,450 email verification credits and 3,200 phone verification credits. In the past 7 days, you've created 3 batches: 'Q1_leads_final.csv' (completed, 2,891 emails verified), 'webinar_signups_march.txt' (still preparing, estimated 1,540 emails), and 'support_contacts.csv' (prepared but not yet launched, estimated cost 890 phone credits). The webinar batch is parsing uploaded data and should finish preparation within a few minutes.

This read-heavy example combines two tools—Get Account Credits and List Batches—to give visibility into available resources and active work. Useful before launching expensive verification runs. Requires API key with read access to account and batch metadata.

@ApexVerify launch verification for batch 'webinar_signups_march' and confirm I want to spend the credits

Verification launched for batch 'webinar_signups_march' (UUID: a3f7c2e1-4b9d-4c8a-9f2e-1d5a6b8c3e4f). This batch contains 1,540 email addresses and will consume approximately 1,540 credits from your account balance. Verification is now running asynchronously; typical completion time for this batch size is 8–12 minutes. You can poll batch status or wait for the process to finish before exporting results.

This action example consumes paid verification credits and is irreversible once launched. Always inspect batch details and account balance first—Launch Batch Verification will fail if credits are insufficient. The MCP enforces deliberate confirmation to prevent accidental spend.

@ApexVerify export the results from my 'Q1_leads_final' batch and summarize which email domains had the highest bounce risk

Exported 2,891 verified records from batch 'Q1_leads_final.csv'. Analyzing the results: 47% of emails were marked deliverable, 31% risky (catch-all or role accounts), and 22% invalid. The highest-risk domains were: generic ISPs like yahoo.com (18% invalid rate), disposable providers such as tempmail.net (94% invalid), and three corporate domains with misconfigured MX records. Deliverable addresses clustered around established enterprise domains—gmail.com, outlook.com, and known SaaS company domains. Consider segmenting risky addresses into a separate nurture track before sending campaigns.

This synthesis example pairs Export Batch Results with AI reasoning to surface actionable patterns. The export itself does not consume credits, but the underlying batch verification did. Useful for turning raw verification data into segmentation or campaign decisions.

When batch verification beats real-time validation for email campaigns

A 6-person growth team preparing a 40,000-contact product launch needs clean email lists before hitting send in their ESP. ApexVerify's batch workflow wins here: upload the CSV, run Prepare Batch to dedupe and estimate cost, check Get Account Credits to confirm budget, then Launch Batch Verification overnight. The Export Batch Results tool delivers structured JSON or XLSX for segmentation—valid addresses go to the ESP, bounces get suppressed, and catch-alls route to a lower-priority sequence. This approach makes sense when you're verifying more than 5,000 contacts at once and can tolerate a 2-12 hour turnaround. If you need sub-second validation at signup or fewer than 1,000 records, a real-time API integration is faster. For quarterly or monthly list scrubs at small-team scale, the batch model keeps verification costs predictable and your deliverability clean.

Scoring inbound leads when phone validity signals intent

A 4-person sales team at a B2B SaaS company uses phone number validity as a lead-quality signal during qualification. Inbound demo requests include mobile numbers, but 30% are fake or disconnected. The team uploads each week's leads as a batch, runs Prepare Batch to normalize formats and flag duplicates, then launches verification to separate working numbers from junk. The Get Batch Details tool shows line-level results—valid mobiles score higher in their CRM, landlines route to a different cadence, and invalid entries get auto-archived. This works when lead volume is 200-2,000 per week and the team reviews batches manually before outreach. If you're verifying one-off contacts during live calls, the batch overhead is too slow. For weekly lead-scoring rituals where phone validity matters more than speed, ApexVerify's batch structure and credit transparency fit the workflow.

Annual contact-database cleanup when compliance drives the timeline

A 3-person operations team at a fintech startup runs an annual audit to document contact-data accuracy for SOC 2 and GDPR readiness. They export 80,000 customer records from their CRM, upload to ApexVerify, and use Prepare Batch to surface duplicate emails and malformed phone numbers without spending credits. The Normalize Data File tool standardizes formats, then they selectively verify high-risk segments—customers flagged for re-engagement or accounts with billing disputes. Export Batch Results generates an XLSX artifact for the auditor showing verification timestamps, validity rates, and suppression counts. This scenario works when the audit is calendar-driven, not transactional, and the team needs a paper trail more than real-time results. If your compliance process requires continuous monitoring or sub-hour SLAs, batch verification is too infrequent. For annual or quarterly audits where documentation and cost control matter, the batch model delivers both.