DataLayer MCP
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TDQS
Scored across 11 tools
Each tool has a clearly distinct purpose with no significant overlap: company-focused tools (employees, headcount, jobs, technographics, enrich, lookup, search) and person-focused tools (enrich, lookup, search) are well-separated, and even within categories (e.g., company_employees vs. company_headcount vs. company_jobs) target different data aspects. The descriptions reinforce these distinctions, making misselection unlikely.
Tool names follow a highly consistent verb_noun pattern throughout, using snake_case uniformly: company_employees, company_headcount, company_jobs, company_technographics, enrich_company, enrich_person, find_intent_signals, lookup_company, lookup_person, search_companies, search_people. This predictability aids agent navigation and understanding.
With 11 tools, the count is well-scoped for a data layer server covering company and person enrichment, search, and intent signals. Each tool earns its place by addressing a specific need (e.g., detailed profiles, filtered searches, headcount breakdowns), avoiding bloat while providing comprehensive coverage for the domain.
The toolset offers complete CRUD-like coverage for the data domain: lookup and search for discovery, enrich for detailed profiles, and specialized tools for headcount, jobs, technographics, and intent signals. There are no obvious gaps; agents can perform end-to-end workflows from finding entities to analyzing their attributes and signals.