# Build brief — a focused alternative to One Place

> **Verdict:** Not faithfully · **Buildability:** 18/100 · **Category:** AI Search
> **Source:** https://www.canitbevibecoded.com/one-place
> Independent editorial assessment from Can It Be Vibe Coded? Not affiliated with, endorsed by, or derived from One Place. Verify current pricing and capabilities before acting.

## Context

**One Place** — AI-powered European real-estate search, boards, lead pipeline, and agentic deal discovery. It currently costs $39/mo.

You can build a scheduled personal property monitor, but not One Place: the value is the maintained real-estate corpus, crawler fleet, AI extraction, deduplication, image/semantic search, geo enrichment, and constant source upkeep across millions of listings.

This brief describes a focused, single-operator replacement for the part of One Place that is genuinely reproducible. It is deliberately narrower than the product it replaces, and it says so in writing. Build the useful core; do not pretend to have rebuilt the rest.

## What you are building

Run saved searches on a schedule, crawl configured source pages, use an LLM API key to extract listing fields, dedupe into SQLite, email matching finds, and expose an MCP server for chat/coding agents.

- Build a focused single-user workflow with real persistence, search, and export.
- A responsive interface with real empty, loading, success, and error states.

## Requirements

### Functional

- Cron-style scheduled search runner.
- MCP server for agent access.

### Data and integrations

- Playwright scraping.
- LLM API key for listing extraction.
- SMTP or Resend email alerts.

Each of these needs a real account, credential, or quota. Set them up before writing feature code.

### Non-functional

- Accessibility: semantic markup, labelled controls, visible focus, and reduced-motion support.
- Security: server-side secrets, validated input, and no credentials in the client bundle.
- Reliability: retries with backoff on external calls, and a clear failure state when a provider is down.
- Portability: the operator can export their data and leave without losing it.

## Implementation brief

Build me a scheduled personal property monitoring agent, the honest consolation
build for One Place: it watches the sources I configure, it does not rebuild a
live nationwide real-estate index. Requirements:

- Node + Express + better-sqlite3 on localhost:4920, with a small web UI for saved
  searches, matches, and lead notes.
- Saved searches live in SQLite: name, source URLs, natural-language criteria, hard
  filters, cadence, email recipients, and last-run time.
- A node-cron runner wakes on each cadence, fetches configured source/search pages with
  Playwright, and stores raw HTML snapshots for debugging.
- Send cleaned listing HTML to an LLM API key from .env and extract strict JSON: title,
  price, currency, surface, rooms, location text, description, image URLs, source URL, and
  confidence.
- Match each extracted listing against the saved search criteria with deterministic
  filters first, then an LLM yes/no explanation for fuzzy preferences like renovation
  potential or sea view.
- Store listings and match decisions in SQLite, dedupe by canonical URL first and fuzzy
  title+price+surface+location second; keep price-change history.
- Email new matches via Resend or SMTP creds in .env, including the match reason, key
  fields, source link, and unsubscribe/disable link for that saved search.
- Include an MCP server exposing tools: list_saved_searches, run_search_now,
  get_recent_matches, explain_match, update_search, and add_lead_note, so Claude/Codex can
  operate it from chat.
- No accounts, no telemetry, binds to localhost only. Out of scope: nationwide coverage,
  anti-bot arms races, paid data resale, mobile apps, and collaborative CRM.
- README: crawler ethics, robots/terms warning, required API/email keys, how to run the
  scheduler, and how to connect the MCP server.

## Delivery standard

- Inspect the repository first, then write a short implementation plan before writing code.
- Deliver the smallest complete end-to-end workflow first; every primary control must work against persisted data.
- Use real validation and storage; never substitute fake dashboards, decorative controls, hard-coded success states, or mock integrations.
- Include responsive layouts plus genuine empty, loading, success, validation, and failure states.
- Keep secrets server-side in environment variables, provide .env.example, and never commit credentials or user data.
- Add structured logs around every external call and return actionable errors without leaking sensitive details.
- Write unit tests for the core logic and one automated test of the main user journey.
- Finish with a README covering setup, architecture, data location, backups, tests, deployment, and known limitations.

## Acceptance criteria

- [ ] A clean install starts the app using only the README and .env.example.
- [ ] The primary journey works from first visit through saved result, reload, edit, export, and deletion where applicable.
- [ ] Invalid input, missing configuration, provider failure, and an empty database each have a usable state.
- [ ] The interface works at 390px and 1440px, is keyboard navigable, and shows visible focus on every control.
- [ ] Tests, type checking, linting, and a production build all pass with no ignored failures.
- [ ] No part of the interface implies a live integration, security guarantee, or scale capability that was not actually built and verified.

## Non-goals

Do not build these, and do not claim to have replaced them:

- Millions of already-normalized listings.
- Maintained crawlers across real-estate portals.
- AI extraction, deduplication, and image/semantic search at scale.
- Geo/POI enrichment and currency/unit normalization.
- The useful dataset is owned, accumulated, or expensive to reproduce.
- Reliability at the vendor's scale is an operations problem, not a prompt.

## What you still own after launch

- Secure credentials, rotate secrets, and handle provider rate limits.
- Run migrations, backups, restores, and dependency updates.
- Test the critical journey after every model, API, or hosting change.
- Monitor failures and fix the edge cases a first prompt will miss.

## Risk

**Operational risk.** The code is achievable; dependable data, integrations, and ongoing operations are the real cost.

Editorial confidence in this assessment: high. No independent one-shot implementation is linked yet.

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Generated by [Can It Be Vibe Coded?](https://www.canitbevibecoded.com) · Full report: https://www.canitbevibecoded.com/one-place