kira-mcp
Ask your AI to find you a flat to rent in Romania — any city, town or commune.
An MCP server (and a CLI) that searches storia.ro, publi24.ro and lajumate.ro live, merges the results, removes duplicates and non-rentals, and reads the ad text for the things the site filters don't give you: heating type, parking, private owner vs agency, and walking distance to a place you care about.
Works with Claude (Code & Desktop), Cursor, VS Code, Windsurf, Gemini CLI, Codex and any other MCP client. Also usable as a plain CLI.
"Find me a 2-room flat in Cluj under 500 €, own boiler, with parking, max 20 minutes on foot from UMF."
$ kira search Brasov --rooms 2 --max-price 500 --heating centrala_proprie --limit 3
Brașov, Brașov — 10 matching, showing 3
storia: ok (74 fetched, 374 on site)
publi24: ok (24 fetched)
lajumate: ok (56 fetched, 382 on site)
1. Studio Maurer Villas partial mobilat
500 EUR | 2 cam | 45 mp | heating: centrala_proprie | parking: included
Tractorul, Brasov, Brasov
https://www.storia.ro/ro/oferta/studio-maurer-villas-partial-mobilat-IDIPoX
2. Apartament pe 2 niveluri, 62 mp, zona Faget-Tractorul
400 EUR | 2 cam | 62 mp | heating: centrala_proprie
...
Why
Romanian rental sites each cover part of the market, their filters are thin, and the details that decide a viewing — centrală proprie or termoficare? is the parking spot included or "posibilitate de parcare în zonă"? — live in free text. kira-mcp does the tab-juggling and the reading, so an agent can answer the question you actually asked.
Features
- All of Romania: 3,181 localities (municipii, orașe, comune) from
Wikidata. Diacritics optional, common shortcuts understood (
cluj,tg mures,buc), ambiguous names resolved (Floresti, Prahova). - 3 sites in parallel, deduplicated across sites (the same flat posted on
two sites shows once, with
also_listed_on). - Filters: price (EUR; RON converted), rooms, heating, parking, private owner, keywords.
- Text extraction tuned on real Romanian ads: heating
(
centrala_proprie/termoficare), parking (included,likely_included,area_possible,none), rooms, surface, floor, street. When a filter needs it, the full ad is read, not just the snippet. - Walking distance from any place (
near="UMF"), geocoded with OpenStreetMap, with a Google Maps directions link. - Drops non-rentals: sale ads, parking-only ads, hotel-style short stays.
- Parking spots search (
search_parking). - Privacy: phone numbers and e-mails are redacted from returned text. The user contacts the owner on the original site.
Quick start (5 minutes)
Step 1 — install uv (once)
kira-mcp runs through uv, which downloads it and its Python on first use. Nothing else to install.
- Windows (PowerShell):
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex" - macOS / Linux:
curl -LsSf https://astral.sh/uv/install.sh | sh
Close and reopen the terminal, then check: uvx --version.
Step 2 — connect it to your AI
claude mcp add kira -s user -- uvx kira-rentals-mcp
Check with claude mcp list → kira: ... ✓ Connected.
- Settings → Developer → Edit Config (opens
claude_desktop_config.json). - Paste (merge with what is there):
{
"mcpServers": {
"kira": {
"command": "uvx",
"args": ["kira-rentals-mcp"]
}
}
}
- Quit Claude Desktop completely (tray icon → Quit) and start it again. "kira" appears under the tools/connectors menu.
If it says the server failed, use the full path of uvx as command
(where uvx on Windows, which uvx on macOS — e.g.
C:\Users\you\.local\bin\uvx.exe).
Same JSON as Claude Desktop, in ~/.cursor/mcp.json,
~/.codeium/windsurf/mcp_config.json or ~/.gemini/settings.json.
.vscode/mcp.json in your workspace:
{
"servers": {
"kira": {
"type": "stdio",
"command": "uvx",
"args": ["kira-rentals-mcp"]
}
}
}
~/.codex/config.toml:
[mcp_servers.kira]
command = "uvx"
args = ["kira-rentals-mcp"]
uvx kira-rentals-mcp --transport streamable-http --port 8000
serves MCP at http://localhost:8000/mcp.
Step 3 — ask
Just talk to it, in English or Romanian:
- "Caută-mi o garsonieră în Sibiu sub 350 €, cu centrală proprie."
- "2-room flat in Timișoara, max 500 €, private owner, sorted by price."
- "Apartamente cu 2 camere în Cluj la max 20 de minute pe jos de UMF."
- "Is parking included in this one? "
- "Loc de parcare de închiriat în Brașov sub 60 €."
The first call takes a few extra seconds while uv downloads the package.
No MCP? Use the agent skill or the CLI
- Agent skill: copy
skills/romania-rentals/into your skills folder (e.g.~/.claude/skills/). It teaches the agent when to search and how to read the results, via the MCP tools or the CLI. - CLI: see below.
Tools
All tools are read-only. Every result carries the original ad URL.
CLI
uvx --from kira-rentals-mcp kira search "Cluj-Napoca" --rooms 2 --max-price 500 --near UMF --max-walk 20 --sort distance
kira search Iasi --heating centrala_proprie --parking included likely_included
kira listing https://www.storia.ro/ro/oferta/...
kira parking Brasov --max-price 80
kira find Floresti
kira --json search Sibiu # machine-readable
Configuration
Sources and limits
kira-mcp does not try to get around a site that blocks it. Results are therefore a large share of the market, not all of it — the tool says so in every response.
Be a good citizen. kira-mcp identifies itself, waits between requests, caches pages for 10 minutes, fetches only what one search needs and returns links back to the sites. It is meant for personal flat-hunting, not bulk harvesting. Check each site's terms before using it for anything else.
Distances are estimates (straight line × 1.3, walking 4.7 km/h). They use the
location the poster entered; an ad with only a neighbourhood gets a
district-precision distance, an ad with neither is listed without one.
Development
git clone https://github.com/Cezart3/kira-mcp && cd kira-mcp
uv sync --group dev
uv run pytest # offline, against synthetic fixtures
KIRA_LIVE=1 uv run pytest -m live # against the real sites
uv run ruff check .
The locality list is rebuilt with uv run python scripts/build_localities.py.
Site parsers live in src/kira_mcp/sites/. Adding a site = one class with
search_rentals and fetch_detail; see sites/base.py.
Credits
- Locality data: Wikidata (CC0).
- Geocoding: Nominatim / © OpenStreetMap contributors (ODbL), at ≤1 request/second, cached.
- Extraction rules grew out of Kira, a personal flat-hunting bot.
License
MIT © 2026 Cezar Tocaciu