Bettercontact

@Bettercontact find leads at Series B SaaS companies with 50-200 employees where the contact is a VP of Sales or Head of Revenue

I've created a Lead Finder search targeting your criteria. The search returned 47 leads matching VP of Sales or Head of Revenue titles at Series B SaaS companies in the 50-200 employee range. Results include LinkedIn profiles, verified work emails for 38 contacts, and direct phone numbers for 29. Top matches include contacts at companies like Acme Analytics, CloudSync Pro, and DataFlow Systems. Each lead record shows job title, company funding stage, employee count, and enrichment confidence scores.

This example shows the MCP's core prospecting workflow — defining audience criteria and retrieving enriched contact data. Each search consumes credits based on the number of leads returned and enrichment depth requested. You'll need sufficient credit balance before running searches, and results quality depends on data availability across BetterContact's provider network.

@Bettercontact enrich this list of 25 LinkedIn profile URLs with work emails and phone numbers, prioritizing email accuracy

I've submitted an enrichment request for your 25 LinkedIn profiles using waterfall enrichment across multiple data providers. The batch is processing now (request ID: req_8x4k9m2p). Preliminary results show 22 work emails found with high confidence, 18 direct phone numbers discovered, and 3 profiles where no contact data was available. I'll retrieve the full results with verification scores and data source attribution once processing completes in approximately 30-45 seconds.

This demonstrates batch enrichment — BetterContact's waterfall approach queries multiple providers to maximize match rates. Each lead enriched consumes credits regardless of whether contact data is found. The MCP supports batches of 1-100 leads per request. Always check your credit balance first, as enrichment costs scale with batch size and can deplete accounts quickly during high-volume operations.

@Bettercontact check my remaining credits, then summarize the enrichment quality from my last Lead Finder search and recommend whether I should run another batch

Your BetterContact account has 1,247 credits remaining. Looking at your most recent Lead Finder search (completed 2 hours ago), you enriched 52 leads with an 81% email match rate and 67% phone match rate — both above BetterContact's typical benchmarks. Given your current credit balance and the strong data quality you're seeing, you have enough runway for approximately 2-3 more searches of similar size before needing to top up. I'd recommend proceeding with your next batch, but consider reducing the lead count to 40-45 to preserve a credit buffer.

This example pairs the MCP's data retrieval with AI reasoning to provide strategic guidance. The AI synthesizes credit balance, historical enrichment performance, and consumption projections to inform your next action. This workflow is valuable for teams managing credit budgets across multiple campaigns, though the AI's recommendations depend on accurate credit tracking and consistent search patterns.

When Bettercontact beats manual LinkedIn scraping for cold outreach

A two-person SaaS startup needs 50 qualified leads per week for cold email. The founder spends 6 hours manually copying LinkedIn profiles into a spreadsheet, then another 3 hours hunting for emails on Hunter or Apollo. Bettercontact collapses that into one API call: Create Lead Finder Search with job title and company size filters, wait 10 minutes, pull enriched contacts with work emails and direct dials via Get Lead Finder Results. The waterfall enrichment hits multiple providers, so match rates run 60-70% instead of the 30% you get from a single tool. This works until you're burning 500+ credits daily—at that scale, you need a dedicated data ops person to manage the API and credit budgets. If you're still in founder-led sales and need to move fast without hiring, Bettercontact turns prospecting from a part-time job into a 20-minute morning ritual.

Why Bettercontact fails for post-conference lead nurture

An 8-person B2B marketing team collects 300 badge scans at a trade show and wants to enrich them for a nurture sequence. They have first names, last names, and company domains—no LinkedIn URLs. Bettercontact's Enrich Leads tool requires a LinkedIn profile URL or a full name plus company name; partial matches don't work reliably. The team ends up manually searching LinkedIn for 40% of the list to grab profile links before they can even call the API. At that point, a tool like Clearbit or ZoomInfo that accepts email or domain as the primary key is faster. Bettercontact shines when you're starting from LinkedIn (sales prospecting, recruiter sourcing), not when you're working backward from event data. If your lead source is badge scans, business cards, or webinar signups, skip this MCP and use a reverse-lookup enrichment provider instead.

When Bettercontact's credit model makes sense for contract recruiting

A 12-person recruiting agency places contract engineers and needs to source 20 passive candidates per role. Each recruiter runs 3-4 searches daily: senior backend engineers at Series B startups, frontend leads at fintech companies, DevOps managers in healthcare. They use Create Lead Finder Search with seniority and department filters, pull 50 profiles per search, then enrich the top 15 with Enrich Leads to get personal emails and mobile numbers. The credit burn is predictable—roughly 200 credits per day per recruiter—and the Check Credits Balance tool lets the ops lead monitor usage without surprise overages. This breaks down if your agency is high-volume (100+ placements per month): at that scale, the per-credit cost adds up faster than a flat-rate data subscription. For boutique agencies placing 8-15 roles per month, Bettercontact's pay-as-you-go model beats paying $500/month for a seat you don't max out.