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Casafari is the AI agent-native real estate data intelligence platform. The most complete property index in Europe: a deduplicated, cleaned property graph of residential and commercial property, for sale and for rent, in 16 countries.The most complete property index in Europe: a deduplicated, cleaned property graph.

How the graph is built

Price-position badge

Show buyers whether each listing is priced above or below the market.

You get: A value on every listing page (API). It uses Comparables, takes 25 tokens a run (€1.00 at €0.04 a token) and runs per listing. For: Portal or classifieds, Software or AI builder.

Status: runs today.

What it does

#StepProductTokens
1comparables_get_comparablesComparables25

One run: 25 tokens, €1.00. Each call costs the same over MCP and REST, so the run always costs what the table says. How many tokens your volume needs, and plans and credits.

Where it runs

Every country the products it uses cover. The plan names a country that one of them does not.

Run in Claude

This playbook calls one Casafari MCP server. Add it to Claude, ChatGPT or any MCP client, and sign in the first time you use it (a Free account, no card, is created then; console).

  • Comparables: https://platform.casafari.com/mcp/comparables

In Claude Code:

bash
claude mcp add --transport http casafari-comparables https://platform.casafari.com/mcp/comparables

Then ask:

text
Run the price-position badge playbook for Spain: call comparables_get_comparables, in that order, and tell me what each step cost in tokens.

Get the API calls

The same steps as REST calls, in order. Create a platform API key in the console and export it as CASAFARI_API_KEY; each call takes the parameters its operation documents in the REST reference.

bash
# 1. Comparables, 25 tokens a call
curl -X POST https://platform.casafari.com/v1/comparables/search \
  -H "Authorization: Bearer $CASAFARI_API_KEY"

Other playbooks

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