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Hunter MCP Server

MCP Server

Natural language access to B2B data via MCP

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About

The Hunter MCP Server bridges the Hunter API with LLM providers that support the Model Context Protocol, enabling users to query B2B data about people and companies using natural language and save results directly into leads.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

Hunter MCP in Claude Desktop

Overview

The Hunter MCP Server bridges the gap between B2B data services and conversational AI by exposing the Hunter API through the Model Context Protocol. Developers who build chat‑based assistants can now query domain information, verify email addresses, and enrich company profiles—all through natural language interactions. This eliminates the need to write custom HTTP clients or manage OAuth flows, allowing teams to focus on building user experiences rather than plumbing.

At its core, the server translates plain‑text prompts into calls to specific Hunter endpoints. For example, a user might ask the assistant, “Find me the email for the marketing director at Acme Corp,” and the server will invoke Hunter’s Email Finder API, return the address, and even create a lead record if requested. This conversational interface turns complex data retrieval into a single, intuitive command that feels like talking to a colleague.

Key capabilities include:

  • Domain Search – Retrieve all contacts associated with a domain, useful for building prospect lists.
  • Email Finder & Verifier – Quickly locate and validate email addresses, reducing bounce rates.
  • Email Enrichment & Company Enrichment – Add context such as job titles, company size, and industry to existing contacts.
  • Lead Creation – Persist enriched data directly into a CRM‑style lead repository, streamlining pipeline management.

These tools are available as MCP commands, so any LLM provider that supports the protocol (Claude Desktop, for instance) can invoke them without additional code. The server also handles authentication by consuming the Hunter API key from environment variables, keeping credentials out of the client side.

Real‑world scenarios range from sales enablement teams automating lead generation to customer support bots that fetch account details on demand. By integrating Hunter’s rich B2B dataset into a conversational loop, organizations can accelerate outreach cycles, improve data quality, and reduce manual entry errors. The Remote MCP Server variant further simplifies deployment by offering a hosted solution that removes local runtime concerns, making it even easier to adopt in production workflows.

Overall, the Hunter MCP Server turns a powerful B2B data platform into a first‑class conversational tool, giving developers a rapid path to richer, data‑driven AI assistants.