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Claude Code Integration

Use DealMachine directly from Claude Code to search properties, find contacts, and build lists using natural language. The DealMachine CLI acts as a Claude Code skill that translates your requests into API calls.

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Setup

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1. Install the CLI

npm install -g @dealmachine/cli

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2. Authenticate

dealmachine login

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3. Use with Claude Code

Once authenticated, you can reference DealMachine data in your Claude Code conversations: 
You: Use the DealMachine API to find properties in Austin, TX
     with high equity that are owned by out-of-state owners.

Claude: I'll use the DealMachine CLI to search for those properties.
        Let me first check what filters are available...

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What the Agent Can Do

Describe the properties you’re looking for and the agent will:
  1. Query the API for available filter fields
  2. Match your description to the correct filters
  3. Execute the search and return results
"Find single family homes in Dallas County worth over $300k
 with at least 60% equity, owned for 10+ years"

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Contact Lookup

Find property owners and their contact information: 
"Get the owners of these 5 properties and their phone numbers"

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Filter Discovery

The agent can help you understand what’s available: 
"What filters can I use to search for distressed properties?"
"Show me all the demographic filters available"

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List Management

Build and manage targeted lists: 
"Create a list called 'High Equity Austin' with these results"
"Add the pre-foreclosure properties to my existing list"

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How Natural Language Filtering Works

The DealMachine API exposes filter field metadata that AI agents use to translate natural language into structured queries: 
Your request:
  "Absentee owners in Austin with 40%+ equity owned 10+ years"

Agent generates:
  {
    "location": { "cities": ["Austin"] },
    "absenteeOwner": true,
    "equityPercent": { "min": 40 },
    "yearsOwned": { "min": 10 }
  }

API returns:
  1,247 matching properties
The agent knows:
  • Available fields — from GET /v1/filters/fields
  • Field types — number ranges, booleans, multi-select options
  • Valid options — property types, MLS statuses, location formats
  • Your context — organization, credits remaining, saved filters

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Best Practices

Begin with a general search and let the agent help you narrow down:
"Find investment properties in Houston"
→ "Now filter to just the ones with pre-foreclosure status"
→ "Show me only the ones owned by individuals, not corporations"
If you’re not sure what’s possible, ask:
"What demographic filters are available?"
"Can I filter by lien amount?"
"What MLS statuses can I search for?"

"How many credits do I have left?"
"How many results would this search return before I export?"
Reference your saved filters by name:
"Run my 'High Equity Austin' filter"
"Update my saved filter to also include multi-family"

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Coming Soon

  • MCP Server — Direct Model Context Protocol integration for any AI agent
  • Batch operations — Process multiple searches in one session
  • Export to tools — Pipe results directly into spreadsheets, CRMs, and mail campaigns
  • Automated workflows — Set up recurring searches that run on a schedule