My entire GTM tech stack (and what each tool does):
Building a GTM engine that doesn't require a 10-person ops team + helps you stop wasting money on Clay Credits.
Here's what powers it:
List Sourcing
- Apollo → Company list building (love filtering by job titles on team)
- AI Ark → AI-powered prospecting
- Discolike → Lookalike audiences & list expansion
- GTME. business → Competitor/partner follower scraping (gauges company maturity)
- Leads on Trees → Newly funded startup data
- Crunchbase → SaaS/investor data for enterprise targeting
- ScrapeCreators → Social scraping
- TopYappers → Influencer data (tiktok + IG)
- LeadsonTrees → Daily Newly funded startups fully enriched.
- CCLeads → coaches and creator biz's
Research & Intelligence
- Serper → Google Search API for Maps, News, general data (~$50/mo vs $500+ traditional)
- Custom RSS feeds (Serper + Google News) → Funding alerts, competitor monitoring
- Spider Cloud → Web scraping at scale
- Apify, Scraping Dog, RapidAPI → Various scraping for cheap (including LinkedIn)
- Job post monitoring → Competitor hiring signals
- TheirStack → historical technology data from sites and job posts
Lead Enrichment (Waterfall System)
- Icypeas → TryKitt → LeadMagic
Sequential email finder with automatic fallback
~$0.005-0.01/email vs $0.50+ on ZoomInfo
- BlitzAPI → LinkedIn enrichment (trialing - extremely promising)
Phone data: Leadmagic + clay waterfall
List Hygiene & Deliverability
- Email Guard → Spam checking
- In-house MX checker → Security gateway detection
- In-house list batching → Send cadence optimization
Outreach
- EmailBison → Campaigns, sequences, deliverability
- Raw Claude+claudecode + custom skill → Copy generation
Sales & Conversion
- Fireflies → Meeting transcription, summaries, content fuel
- Gamma → AI-generated proposals & custom client resources
- Tella → Personalized VSLs & 1:1 video outreach
Content & Distribution
- Any CRM tbh.
Knowledge & Client Management
- GitHub + Git worktrees → Client knowledge bases in markdown
- Fireflies. ai → Feeds content creation + improves knowledge base over time
- Google Workspace → Deliverables
- GitBook → Client-facing knowledge sharing
Raw Infrastructure
- Supabase → Database backend
- OpenRouter → LLM API routing (pay per token, not per seat)
- Trigger. dev → Background jobs & automation
n8n → Workflow automation (self-hosted = $0)
- Trigify → socail data -> Slowly replacing with in-house solutions
- Bright data → Disgustingly good proxies and data unblockers
- Snowflake → Tons of free bulk data
The glue: Claude Code and Clay
Skills (SOPs as code) tie everything together. One command can:
- Conduct research
- Qualify companies, format data
- Programmatically search Supabase to pull leads
- Spintax and spam check copy iteratively.
Whereas Clay has extreme concurrency, and useful tools built in.
The individual tools are commodities. The orchestration layer is the multiplier.
Building a scraping stack from scratch.
Here's what we actually use across hundreds of outbound campaigns:
Instantly Data Scraper — directories.
When you need to pull from G2, Capterra, industry lists. Fast. No code.
Playwright + Claude Code — custom sites.
Anything with a weird structure or login wall. Claude writes the scraper. You run it.
Firecrawl — full site crawls.
When you need everything on a domain. Pricing pages, case studies, team pages. 10 minutes, not 10 hours.
Jina / https://t.co/pAKTBWthlG — scale.
10K+ pages. LLM-ready output. This is where most teams underinvest.
Browserbase — agentic browsing.
For flows a static scraper can't handle. Session persistence. Works where everything else breaks.
BrightData — bot-protected sites.
Yes it costs more. Yes it's worth it. LinkedIn. Amazon. Anything that actively fights you.
Finding the directories is one thing, understanding the use case and framing is another thing.
A company listed on a niche directory already told you something.
They chose to be found. They're actively positioning in that category. They want buyers to discover them. That's not a cold lead anymore.
Apollo gives you a list of people who fit a description.
Directories give you a list of people who took action.
Those are not the same signal.
Most funded teams spend 3 weeks debating which database to use.
Then overpay for ZoomInfo since that’s what they did at their last company.
The teams booking meetings on day one?
They scraped intent from niche directories before anyone else thought to.
A client recently funded their Series A. Board wanted a consistent pipeline in 90 days.
We skipped the generic Apollo list.
Scraped 5,600 schools from vertical-specific directories.
Matched them against relevant signals.
Sent 7,000 emails. Booked 55 meetings in 31 days.
Same offer. Same copy.
Different list quality.
The scraping stack matters.
But knowing where to point it matters more.
Directories are intent. Treat them that way.
@MitchellKeller_ MCPs are great for normies who want to use chatgpt/chatbot UIs. It will make a comeback only because of security as the protocol becomes more mature.