AI Agents + Data Enrichment

AI agents are changing how teams interact with data. Instead of manually calling APIs or uploading spreadsheets, you can now tell an AI agent to "find Sarah Chen's email at TechCorp" or "enrich all contacts from last week's webinar" and it handles the rest.

This is made possible by the Model Context Protocol (MCP). A standard that lets AI assistants connect to external tools and APIs. Enrich offers a native MCP server that works with Claude, OpenAI's ChatGPT, Google's Gemini, Cursor, and VS Code.

The result: data enrichment becomes a conversation, not a workflow.

MCP (Model Context Protocol) is an open standard developed by Anthropic that allows AI models to use external tools. An MCP server exposes specific capabilities, like "find an email" or "enrich a person") that AI agents can call autonomously.

When you connect the Enrich MCP server to your AI assistant, it gains the ability to:

• Find professional email addresses from name + company
• Validate email addresses
• Look up phone numbers
• Perform reverse email lookups
• Search for leads at target companies

The AI agent decides when and how to use these tools based on your instructions. No API key management, no code, just natural language.

To connect Enrich to Claude Desktop or Claude Code:

1. 1Get your API key from dash.enrich.so
2. 2Add the Enrich MCP server to your Claude configuration
3. 3Start a conversation and ask Claude to enrich data

• "Find the email address for Jane Smith at Stripe"
• "Enrich this list of emails and give me their job titles"
• "Validate these 50 email addresses and tell me which ones are invalid"
• "Look up the company data for everyone at acme.com"

Claude will call the Enrich API automatically and present the results in a readable format.

Sales research: Ask your AI agent to research a prospect before a call. "Tell me everything about john@acme.com" returns their full profile, company details, and social links, all enriched in real-time.

CRM cleanup: "Find all contacts in this spreadsheet that have invalid emails". The AI validates each email and flags the bad ones.

Lead qualification: "Which of these leads work at companies with 100+ employees?". The AI enriches company data and filters by size.

Outbound prospecting: "Find the VP of Engineering at these 20 companies". The AI uses the Lead Finder and Email Finder APIs to build a targeted list.

Meeting prep: Before a sales call, ask "What can you tell me about sarah@techcorp.io?" and get a complete briefing in seconds.

Even without MCP, you can integrate Enrich into AI-powered applications:

• Function calling: OpenAI and Anthropic support function calling, define Enrich API endpoints as functions your AI can call
• RAG pipelines: Enrich contact data before storing it in your vector database for richer retrieval
• Agent frameworks: LangChain, CrewAI, and AutoGen can use Enrich as a tool in multi-step agent workflows
• VS Code / Cursor: Use the MCP server within your IDE to enrich data while coding

The Enrich API returns structured JSON, which AI models can parse and reason about natively. No special formatting or adapters needed.