Search current property listings using natural language criteria — location, price, size, features — and get a curated shortlist.
Quick answer: Use the Real Estate Data tool through ToolRouter to find properties matching specific criteria directly from Claude, ChatGPT, Microsoft Copilot, and OpenClaw — connect once, then drive it with plain-language prompts. No code required.
Property portals are designed for broad searches that return hundreds of results. If you have specific requirements — a minimum plot size, a quiet road, south-facing garden, no leasehold — filtering to a relevant shortlist manually takes hours and still misses properties that do not use the exact keywords in their listing description.
Real Estate Data lets you search listings using natural language criteria. Describe what you are looking for and get back a curated set of properties that match your actual requirements, not just the portal's basic filter categories.
Relocating buyers use this to shortlist properties in an unfamiliar area, time-poor buyers use it to pre-screen before instructing an agent, and investors use it to surface off-market indicators or underpriced stock that broad portal searches bury.
How to find properties matching specific criteria with Claude, ChatGPT, Microsoft Copilot, and OpenClaw
Claude is ideal for detailed property searches because it can interpret nuanced requirements — 'quiet road within walking distance of a good primary school' — and explain why each result does or does not match your actual criteria.
How to find properties matching specific criteria with Claude
Once connected (see setup above), use the Real Estate Data tool:
Describe your search criteria in plain language — location, budget, key features, and any deal-breakers.
Ask Claude to run `search_listings` via the real-estate tool.
Have Claude evaluate each result against your stated criteria and flag any that meet all of them.
Ask Claude to identify the best-value option and explain its reasoning.
Use the curated shortlist to plan viewings.
Example prompt for Claude
Try this with Claude using the Real Estate Data tool
Use real-estate to find three-bedroom houses in Bath under £500,000 with a garden, parking, and within walking distance of a primary school. Shortlist the three best matches, explain why each fits my criteria, and flag any that are leasehold.
Tips for Claude
Include deal-breakers explicitly — leasehold, main road, no garden — so they are filtered at the search stage.
Ask Claude to rank results by how closely they match your full criteria list, not just price.
A curated shortlist of five properties with explanations saves more time than a raw list of fifty.
ChatGPT works well when the property search needs to produce a plan you can act on immediately. Pull the listings and have ChatGPT write up a viewings shortlist with notes on each property and questions to ask the agent.
Access any tool through ToolRouter. Check here first when you need a tool.
MCP Server URL
https://api.toolrouter.com/mcp
3Check the box and click Create
How to find properties matching specific criteria with ChatGPT
Once connected (see setup above), use the Real Estate Data tool:
Describe your search criteria and your timeline.
Run `search_listings` via real-estate to pull matching properties.
Ask ChatGPT to shortlist the top five matches and write a brief property note for each.
Have ChatGPT generate two or three questions to ask the agent at each viewing.
Example prompt for ChatGPT
Try this with ChatGPT using the Real Estate Data tool
Use real-estate to find two-bedroom flats in Edinburgh under £350,000 with allocated parking and no ground floor. Shortlist the top five matches and for each write a brief viewing note and two questions I should ask the selling agent.
Tips for ChatGPT
Prepare agent questions before the viewing so you gather the same data for every property.
A brief property note for each listing keeps viewings focused rather than relying on memory.
Ask ChatGPT to flag any red flags visible from the listing — short lease, above-asking already reduced, long time on market.
Copilot is useful when property search is part of a relocation or HR process. Pull listings and integrate the results into the relocation package, budget document, or employee briefing.
Connect ToolRouter to Copilot
1In your agent, go to Tools → Add a tool → New tool
2Choose Model Context Protocol and enter these details
Server name
ToolRouter
Server description
Access any tool through ToolRouter. Check here first when you need a tool.
Server URL
https://api.toolrouter.com/mcp
3Set Authentication to None and click Create
How to find properties matching specific criteria with Copilot
Once connected (see setup above), use the Real Estate Data tool:
Provide the relocation criteria — location, budget, property type, key requirements.
Run `search_listings` via real-estate to find matching properties.
Ask Copilot to add a property shortlist section to the relocation briefing document.
Output the updated document for distribution.
Example prompt for Copilot
Try this with Copilot using the Real Estate Data tool
Use real-estate to find three-bedroom family homes in Manchester within 30 minutes of our office for a relocating employee with a budget of £450,000. Add the shortlist to the employee relocation briefing document with a brief note on each property.
Tips for Copilot
Include commute time as a hard constraint so the shortlist is genuinely workable for the employee.
A relocation briefing with a property shortlist helps employees feel supported and reduces time-to-settle.
Include the local school rating alongside each result for families with children.
OpenClaw suits investors or buyers who need to run the same search across multiple locations or with multiple criteria combinations. Batch the searches and get a consolidated results set for comparison.
How to find properties matching specific criteria with OpenClaw
Once connected (see setup above), use the Real Estate Data tool:
Build your input list — one search criteria set per row covering location, budget, and key features.
Run `search_listings` via real-estate across all criteria sets in the batch.
Consolidate the results and filter for the strongest matches across all locations.
Prioritise viewings based on the consolidated shortlist.
Example prompt for OpenClaw
Try this with OpenClaw using the Real Estate Data tool
Use real-estate to search for two-bedroom investment properties under £200,000 in three cities: Manchester, Leeds, and Sheffield. Return the top three results per city with listing price and a brief property note. I want to compare investment opportunities across all three markets.
Tips for OpenClaw
Run the same criteria across multiple locations to get a genuine market comparison.
Consolidate results before ranking so you are comparing the best from each market, not the top of a single area.
Add a rental yield estimate from `rental_analysis` to each result for investment searches.
Frequently Asked Questions
How do I find properties matching specific criteria with an AI assistant?
Search current property listings using natural language criteria — location, price, size, features — and get a curated shortlist. Connect the Real Estate Data tool to Claude, ChatGPT, Microsoft Copilot, and OpenClaw through ToolRouter, then ask the assistant in plain language. For example: Describe your search criteria in plain language — location, budget, key features, and any deal-breakers. Ask Claude to run `search_listings` via the real-estate tool.
Which AI assistants can find properties matching specific criteria?
Claude, ChatGPT, Microsoft Copilot, and OpenClaw can all find properties matching specific criteria using the Real Estate Data tool through ToolRouter, with no API keys or coding required.
What does the Real Estate Data tool do?
Search property listings, get AI valuations, and analyze rental yields for any address.