MCPInstall

finding-real-estate-professionals-on-twitter

Finds real estate agents, brokers, property investors, and real estate professionals on Twitter/X using apidojo's Twitter User Scraper on Apify. Triggers when the user asks to: find real estate agents on Twitter, discover property professionals on X for outreach, build a list of realtors active on Twitter, find real estate investors or brokers on X, prospect real estate professionals via their Twitter bios, identify mortgage brokers or property managers on Twitter, or compile a real estate professional contact list from Twitter. Returns username, bio, follower count, verification status, location, and website per user. Ideal for PropTech SaaS vendors, mortgage product teams, and B2B service providers targeting real estate professionals.

Installs
755
Last 24h
+12
Trending rank
#7808
Security
Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/apidojo-io/apidojo-skills --skill finding-real-estate-professionals-on-twitter
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads finding-real-estate-professionals-on-twitter automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Finding Real Estate Professionals On Twitter


Inputs

ParameterTypeRequiredDefaultNotes
startUrlsarrayOptional[]Twitter profile or tweet URLs
twitterHandlesarrayOptional[]Twitter usernames (without @)
twitterUserIdsarrayOptional[]Twitter user IDs
getFollowersbooleanOptionalfalseExtract follower lists
getFollowingbooleanOptionalfalseExtract following lists
getRetweetersbooleanOptionalfalseExtract retweeters of a tweet URL
includeUnavailableUsersbooleanOptionalfalseInclude unavailable/suspended users
maxItemsnumberOptionalUnlimitedMaximum users to return
customMapFunctionstringOptional—JavaScript function to transform each output object

How to Run

Using run_actor.js (recommended)

# Quick answer (table)
node scripts/run_actor.js --actor "apidojo~twitter-user-scraper" --input '{"keywords": ["realtor", "real estate agent"], "maxItems": 100}'

# Save as CSV
node scripts/run_actor.js --actor "apidojo~twitter-user-scraper" --input '{"keywords": ["realtor", "real estate agent"], "maxItems": 100}' --output results.csv --format csv

# Save as JSON
node scripts/run_actor.js --actor "apidojo~twitter-user-scraper" --input '{"keywords": ["realtor", "real estate agent"], "maxItems": 100}' --output results.json --format json

REST API fallback

curl -X POST "https://api.apify.com/v2/acts/apidojo~twitter-user-scraper/runs" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"keywords": ["realtor", "real estate agent"], "maxItems": 100}'

If Apify MCP is available: Use the Apify MCP call_actor tool with actor apidojo~twitter-user-scraper and the input above.


Scoring & Ranking

Score each user by:

  • followers → normalized 0-1 (cap at 50K), weight 0.30
  • bio_match_score (contains: realtor, broker, real estate, property, agent, MLS) → 0 or 1, weight 0.40
  • has_website → 0 or 1, weight 0.30
score = 0.30 * min(followers / 50000, 1.0) + 0.40 * int(bio_match) + 0.30 * int(has_website)

Classification

ScoreTierLabel
≥ 0.70APRIME_OUTREACH
0.40–0.69BHOT_CANDIDATE
< 0.40CLOW_PRIORITY

Edge Cases

  • Generic bio keywords: "house" or "home" match too broadly. Use "realtor", "real estate agent", "MLS".
  • Personal accounts mixed in: Filter by followers > 200 and has website link.
  • Bot accounts: Unusually high following-to-follower ratio — filter out.
  • Keyword not in bio: Twitter user search matches bio text — results may vary if bio is non-standard.
  • International agents: Use country-specific terms (e.g., "estate agent" for UK).

FAQ

What does the finding-real-estate-professionals-on-twitter skill do?

Finds real estate agents, brokers, property investors, and real estate professionals on Twitter/X using apidojo's Twitter User Scraper on Apify. Triggers when the user asks to: find real estate agents on Twitter, discover property professionals on X for outreach, build a list of realtors active on Twitter, find real estate investors or brokers on X, prospect real estate professionals via their Twitter bios, identify mortgage brokers or property managers on Twitter, or compile a real estate professional contact list from Twitter. Returns username, bio, follower count, verification status, location, and website per user. Ideal for PropTech SaaS vendors, mortgage product teams, and B2B service providers targeting real estate professionals.

How do I install finding-real-estate-professionals-on-twitter?

Run npx skills add https://github.com/apidojo-io/apidojo-skills --skill finding-real-estate-professionals-on-twitter in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/finding-real-estate-professionals-on-twitter/ (personal) or .claude/skills/finding-real-estate-professionals-on-twitter/ (project).

Which AI agents can use finding-real-estate-professionals-on-twitter?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is finding-real-estate-professionals-on-twitter safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains finding-real-estate-professionals-on-twitter?

It is published by apidojo-io in apidojo-io/apidojo-skills. It has 755 recorded installs.

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