gaff-check
Enables AI agents to perform due diligence on Irish properties by querying public datasets for planning applications, sold prices, flood risk, radon risk, and zoning.
README
gaff-check
Due diligence on any Irish property, for AI agents.
gaff-check is an open-source MCP (Model Context Protocol) server that gives AI assistants — Claude, Cursor, ChatGPT, or any MCP-compatible agent — ground truth from Ireland's scattered public property datasets.
Ask your assistant:
"Should I bid on this bungalow in Killiney? Tell me everything I should worry about."
…and it can check, in one conversation:
- 🏗️ Planning applications near the property (that pending apartment block behind the back garden)
- 💶 Sold prices on the street and in the area (Property Price Register)
- 🌊 Flood risk (OPW / GSI flood mapping)
- ☢️ Radon risk (EPA radon risk areas)
- 🗺️ Zoning (Myplan generalised land-use zoning)
- ⚡ BER / energy rating context and retrofit grant signals (phase 2)
All from official, public Irish datasets. No scraping of commercial listing sites. No estimates — records.
Why
Buying (or renovating, or just being nosy about) a house in Ireland means trawling six-plus government websites, each with its own dreadful UX, none of which talk to each other. The data is public. The synthesis isn't. gaff-check is the glue: a single, boring, reliable tool layer so the reasoning can happen in your AI assistant.
What it is not
- Not a valuation engine. It returns records; your agent does the thinking.
- Not a Daft/MyHome scraper. Public state data only.
- Not a website. It's a utility that enhances tools you already use.
Quick start (target UX)
npx gaff-check # stdio MCP server
Claude Desktop config:
{
"mcpServers": {
"gaff-check": { "command": "npx", "args": ["-y", "gaff-check"] }
}
}
Status
Pre-alpha. See SPEC.md for the design and docs/DATA_SOURCES.md for the data plumbing.
Licence
MIT. Data returned by the tools is subject to the licences of the underlying public datasets (mostly CC-BY 4.0 / PSI) — see DATA_SOURCES.md.
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