Prospect ICP Search

Search for prospects matching an Ideal Customer Profile using natural language. This skill translates human-friendly buyer descriptions into structured Amplemarket API queries and returns formatted results.

Instructions

When a user describes their ideal prospect in natural language, follow these steps to execute a precise search using the Amplemarket MCP tools.

Steps

1. Parse the user's criteria into structured filters:

• Titles (e.g., "VP of Sales", "Head of Marketing")
• Seniority levels (map to enums: "Owner", "Founder", "C-Suite", "Partner", "VP", "Head", "Director", "Manager", "Senior", "Entry", "Intern", "Other")
• Person locations (cities, states, countries, max 10)
• Departments (map to enums: "Senior Leadership", "Design", "Education", "Consulting", "Engineering & Technical", "Finance", "Human Resources", "Information Technology", "Legal", "Marketing", "Operations", "Revenue", "Medical & Health", "Product")
• Company names or domains
• Company locations
• Company industries (resolve via step 2)
• Company sizes (map to enums: "1-10 employees", "11-50 employees", "51-200 employees", "201-500 employees", "501-1000 employees", "1001-5000 employees", "5001-10000 employees", "10001+ employees")
• Company types (map to enums: "Public Company", "Educational", "Self Employed", "Government Agency", "Non Profit", "Self Owned", "Privately Held", "Partnership")

1. Resolve industries and job functions by calling:

• mcp__claude_ai_Amplemarket__get_industries to get the list of valid industry values and match the user's description to the closest ones.
• mcp__claude_ai_Amplemarket__get_job_functions to get valid job function values if the user specifies functional areas.

1. Execute the search by calling mcp__claude_ai_Amplemarket__search_people with the mapped parameters. Set full_output to true for detailed results. Start with page_size of 10 unless the user requests more.
2. Format the results as a clean table with columns:

• Name
• Title
• Company
• Location
• LinkedIn URL

1. Offer next actions after presenting results:

• "Would you like me to enrich any of these prospects for full contact details?"
• "Should I create a lead list from these results?"
• "Want me to expand the search with different criteria or load more results?"

Important Notes

• Always resolve industries and job functions from the API before searching. Do not guess enum values.
• If the user's criteria are ambiguous, ask for clarification before searching.
• When location is specified as a broad region (e.g., "Europe"), break it into specific countries.
• If the search returns zero results, suggest relaxing one filter at a time and explain which filter is most likely too restrictive.

Examples

Example 1: Role + Industry + Location + Size

User prompt: "Find me VP of Sales at fintech companies in New York with 50 to 200 employees"

What the skill does:

1. Calls mcp__claude_ai_Amplemarket__get_industries to find the correct fintech industry value.
2. Calls mcp__claude_ai_Amplemarket__search_people with:

• person_titles: ["VP of Sales"]
• person_seniorities: ["VP"]
• person_locations: ["New York, US"]
• company_industries: [matched fintech industry value]
• company_sizes: ["51-200 employees"]
• full_output: true

1. Returns a formatted table of matching prospects.

Example output:

Found 47 total results. Showing page 1 of 5.

Would you like me to:

• Enrich any of these prospects for email and phone?
• Create a lead list from all 47 results?
• See the next page of results?

Example 2: Department + Seniority + Company Type

User prompt: "Search for marketing directors at publicly traded SaaS companies in the Bay Area"

What the skill does:

1. Calls mcp__claude_ai_Amplemarket__get_industries to resolve SaaS/Software industry values.
2. Calls mcp__claude_ai_Amplemarket__search_people with:

• person_titles: ["Marketing Director", "Director of Marketing"]
• person_seniorities: ["Director"]
• person_departments: ["Marketing"]
• person_locations: ["San Francisco Bay Area, US"]
• company_types: ["Public Company"]
• company_industries: [matched SaaS/Software values]
• full_output: true

Example 3: Multi-Title Search with Company Size

User prompt: "Look up Heads of Engineering and CTOs at startups with 11-50 employees in London and Berlin"

What the skill does:

1. Calls mcp__claude_ai_Amplemarket__search_people with:

• person_titles: ["Head of Engineering", "CTO", "Chief Technology Officer"]
• person_seniorities: ["Head", "C-Suite"]
• person_departments: ["Engineering & Technical"]
• person_locations: ["London, UK", "Berlin, DE"]
• company_sizes: ["11-50 employees"]
• full_output: true

Troubleshooting