find-similar

name	find-similar
description	Find companies or contacts similar to a given reference. Provide a company name/domain or a person's name/email and get a ranked list of lookalikes scored by similarity. Useful for territory expansion, TAM analysis, competitive mapping, expanding buyer networks, and building targeted prospecting lists.

Find Similar

Find companies or contacts similar to a reference entity using ZoomInfo's ML-powered similarity model.

Input

The user will provide via $ARGUMENTS:

• For companies: a company name, domain, or ZoomInfo company ID
• For contacts: a person's name and company (e.g., "Jane Smith at Acme Corp"), email address, or ZoomInfo person ID
  • Optionally: a target company to scope results to (e.g., "at Microsoft" or "within Salesforce")
  • Optionally: how many results they want (defaults to 25, max 100)

Determine whether the user is looking for similar companies or contacts based on what they provide, then follow the appropriate workflow below.

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Company Workflow

1. Lookup metadata first — before calling any other MCP tool, use lookup to load reference data for any fields relevant to the request. Use the returned id values (not display names) in all subsequent API calls.

2. Find similar companies using find_similar_companies. This returns up to 100 results ranked by similarity score.

   • If you have a ZoomInfo company ID, pass companyId.
   • If you only have a company name, pass companyName — the API can resolve it directly.

Company Output Format

Similar companies to [Reference Company Name]:

Rank	Company	Industry	Employees	Revenue	Country	Similarity Score
1
2
...

Show the top 25 by default. If the user asks for more, show up to 100.

After the table:

• Note the total number of similar companies returned
• Call out any patterns (e.g., "heavily weighted toward mid-market SaaS in North America")
• Suggest next steps: use /zoominfo:enrich-company to get full details on any result, or /zoominfo:find-buyers to identify contacts at a target

---

Contact Workflow

1. Lookup metadata first — before calling any other MCP tool, use lookup to load reference data for fields relevant to interpreting the results:

   • lookup with fields: [{"fieldName": "management-levels"}, {"fieldName": "departments"}, {"fieldName": "job-functions"}]
   • Use the returned id values (not display names) in all subsequent API calls and for categorizing results.

2. Resolve the reference person if the user did not provide a ZoomInfo person ID:

   • If the user gave an email → use enrich_contacts with email to get the person's ZoomInfo person ID.
   • If the user gave a name and company → use enrich_contacts with firstName, lastName, and companyName to get the person's ZoomInfo person ID.
   • If enrichment fails, fall back to search_contacts with fullName and companyName to find a match.
   • Extract the ZoomInfo person ID from the result.

3. Resolve the target company if the user specified one:

   • Use search_companies with companyName or companyWebsite to get the ZoomInfo company ID — use lookup id values for any filters.

4. Find similar contacts using find_similar_contacts with:

   • referencePersonId: the resolved ZoomInfo person ID (required)
   • targetCompanyId: the resolved ZoomInfo company ID (only if the user specified a target company)
   • pageSize: user-specified count or 25

Contact Output Format

Reference Person

[Full Name] — [Title] at [Company] Brief profile summary: department, management level, job function. This anchors the similarity analysis.

Similar Contacts

Rank	Name	Title	Company	Department	Management Level	Score
1
2
...

Show the top 25 by default. If the user asks for more, show up to 100.

For each contact, use the meta field from the response to explain WHY they are a match. The meta describes the reference person used to form the similarity — use this to connect the recommendation back to the reference person's attributes.

Pattern Analysis

• By Title/Function: What roles dominate the results? (e.g., "Heavily weighted toward revenue operations and sales leadership")
• By Seniority: What management levels appear most? Use the lookup values to categorize accurately.
• By Company Profile: What types of companies do these contacts work at? (e.g., "Mostly mid-market SaaS, 200-1000 employees")
• If scoped to a target company: Note which departments and levels within that company have the strongest matches.

After the table:

• Note the total number of similar contacts returned
• Call out any patterns in the results
• Suggest next steps: use /zoominfo:enrich-contact to get full details on any result, or /zoominfo:find-buyers to identify other contacts at a specific company from the list