The Problem
Multiple subreddits posted the same week about a B2B real estate AI search agent built in 2 days with Claude Code. The bottleneck on every variation is the data layer — direct MLS access costs $300-1,000/mo per market plus broker sponsorship.
The Scavio Solution
Replace MLS sponsorship with Scavio's SERP + Reddit endpoints. Brokerage discovery via SERP, sentiment via Reddit, market news via Google News. Covers 80% of the B2B prospecting signal at a fraction of MLS cost.
Before
$300-1,000/mo MLS access per market, manual broker sponsorship process, signal limited to active listings.
After
$30/mo Scavio Project tier, full multi-market coverage, broader signal including hiring and sentiment.
Who It Is For
B2B sales teams selling into real estate brokerages, recruiters, real estate SaaS founders, marketing agencies serving brokers.
Key Benefits
- 80% MLS signal at <10% cost
- Multi-market coverage from one key
- Reddit sentiment layer that MLS lacks
- MCP-driven Claude Code build
- Two-day build vs months of MLS onboarding
Python Example
import os, requests
H = {'x-api-key': os.environ['SCAVIO_API_KEY']}
def prospects(city):
return {
'serp': requests.post('https://api.scavio.dev/api/v1/search', headers=H, json={'query': f'real estate brokerage {city}'}).json(),
'reddit': requests.post('https://api.scavio.dev/api/v1/reddit/search', headers=H, json={'query': f'{city} broker'}).json(),
}JavaScript Example
const H = { 'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json' };
async function prospects(city) {
const [s, r] = await Promise.all([
fetch('https://api.scavio.dev/api/v1/search', { method:'POST', headers:H, body: JSON.stringify({ query: `real estate brokerage ${city}` }) }).then(r => r.json()),
fetch('https://api.scavio.dev/api/v1/reddit/search', { method:'POST', headers:H, body: JSON.stringify({ query: `${city} broker` }) }).then(r => r.json())
]);
return { s, r };
}Platforms Used
Web search with knowledge graph, PAA, and AI overviews
Community, posts & threaded comments from any subreddit