Full ICP-to-leads pipeline. Describe your ideal customer in plain English and get a ranked table of enriched decision-maker leads with emails and phone numbers.

Prospect Go from an ICP description to a ranked, enriched lead list in one shot. The user describes their ideal customer via "$ARGUMENTS". Examples /apollo:prospect VP of Engineering at Series B+ SaaS companies in the US, 200 1000 employees /apollo:prospect heads of marketing at e commerce companies in Europe /apollo:prospect CTOs at fintech startups, 50 500 employees, New York /apollo:prospect procurement managers at manufacturing companies with 1000+ employees /apollo:prospect SDR leaders at companies using Salesforce and Outreach Step 1 — Parse the ICP Extract structured filters from the natural language description in "$ARGUMENTS": Company filters: Industry/vertical keywords → q organization keyword tags Employee count ranges → organization num employees ranges Company locations → organization locations Specific domains → q organization domains list Person filters: Job titles → person titles Seniority levels → person seniorities Person locations → person locations If the ICP is vague, ask 1 2 clarifying questions before proceeding. At minimum, you need a title/role and an industry or company size. Step 2 — Search for Companies Use mcp claude ai Apollo MCP apollo mixed companies search with the company filters: q organization keyword tags for industry/vertical organization num employees ranges for size organization locations for geography Set per page to 25 Step 3 — Enrich Top Companies Use mcp claude ai Apollo MCP apollo organizations bulk enrich with the domains from the top 10 results. This reveals revenue, funding, headcount, and firmographic data to help rank companies. Step 4 — Find Decision Makers Use mcp claude ai Apollo MCP apollo mixed people api search with: person titles and person seniorities from the ICP q organization domains list scoped to the enriched company domains per page set to 25 Step 5 — Enrich Top Leads Credit warning : Tell the user exactly how many credits will be consumed before proceeding. Use mcp claude ai Apollo MCP apollo people bulk match to enrich up to 10 leads per call with: first name , last name , domain for each person reveal personal emails set to true If more than 10 leads, batch into multiple calls. Step 6 — Present the Lead Table Show results in a ranked table: Leads matching: [ICP Summary] Name Title Company Employees Revenue Email Phone ICP Fit ICP Fit scoring: Strong — title, seniority, company size, and industry all match Good — 3 of 4 criteria match Partial — 2 of 4 criteria match Summary : Found X leads across Y companies. Z credits consumed. Step 7 — Offer Next Actions Ask the user: 1. Save all to Apollo — Bulk create contacts via mcp claude ai Apollo MCP apollo contacts create with run dedupe: true for each lead 2. Load into a sequence — Ask which sequence and run the sequence load flow for these contacts 3. Deep dive a company — Run /apollo:company intel on any company from the list 4. Refine the search — Adjust filters and re run 5. Export — Format leads as a CSV style table for easy copy paste