Paris Compass Mcp

io.github.IvandeMurard由 GitHub 帳號 IvandeMurard 發布v0.1.4更新於 Oct 24, 2026

Paris commercial premises from open data: shopfront history, street turnover, sourced figures.

概覽

AI 產生的概覽

一個唯讀的 MCP 伺服器,讓助理查詢巴黎商業店面:店面歷史、商譽成交價、街區更替情況以及周邊與環境指標。

可以做什麼
追溯店面歷史:某地址的歷任用家、商譽轉讓和破產公告,每項都附來源、日期和信賴等級(已確證、相互印證、可能、未定)。依業種和街道比較商譽成交價,給出中位數區間而非單一數字。讀取橫跨三次普查統計的街道更替率與存活率,未取得授權的普查年份資料會被隱去。考察 800 公尺範圍內的周邊設施:學校、醫療、餐飲、公園和交通,並彙整為步行便利度。查看環境指標:實測空氣品質、1 公里內的自然與技術風險,以及標示為估算的噪音和人流代理指標。
適用情境
適合在巴黎簽訂商業租約前使用,了解某地址曾經營什麼、商譽成交價多少、是否已有廚房設施,或某條街相對於同業種和同街區的表現如何。也適合助理就單一地址做深入分析,而非批次篩選投資組合。
執行需求
以 npm 套件形式透過 npx 在本機執行,需要 Node.js。無需帳號或金鑰:伺服器自帶公開的 Compass 專案並匿名讀取。SUPABASE_URL 和 SUPABASE_ANON_KEY 為選用項目,僅在讀取其他衍生 Supabase 專案時需要。需要連網存取託管資料庫。
安裝前請注意
雖為唯讀,但它匿名查詢託管的 Supabase 專案,所查地址會傳送給該第三方。若設定 SUPABASE_ANON_KEY,只能使用匿名發布金鑰,切勿使用服務角色或付費金鑰。部分資料因授權因素被隱去,部分標示為「可能」或「估算」,應視為帶信賴度的證據而非已核實事實。涵蓋範圍限於巴黎市區,README 說明地圖展示尚未接入完整資料集。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Paris Compass Mcp,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

Compass

Before you sign a lease, read the street.

What traded at this address, how the street turns over, what goodwill sold for. Public sources only, every figure cited.

[Demo] [Scope] [Data] [Eval gate] [MCP] [License] [Stack]

Open the demo → · no account needed · pre-recorded addresses, 17th arrondissement

For an agent → npx -y paris-compass-mcp · six tools, read-only, on the hosted corpus


The question

You are standing in front of an empty shopfront. The agent says the street is lively.

Compass answers on six axes at once.

What was here10 rue Mandar, 2e: an Asian restaurant in the 2023 census, and six goodwill sales at that street number since 2017
How the street behavesturnover and survival by trade, measured across three censuses — withheld until the 2017 and 2020 licences are cleared
What it costsmedian fonds between 160 000 and 170 000 €, 220 000 € for a café
What is moving nowan insolvency filed here is public months before any listing
What is around itschools, healthcare, food, parks and transit counted within 800 m, aggregated into walkability
What the environment is worthair quality measured (Copernicus), natural and technological risks within 1 km, noise modelled from major roads at 500 m

Each of those arrives with its source, its date and its confidence level.

Note the wording, because the product keeps it too: air quality is measured, noise is modelled. Noise and footfall are proxies, labelled as such on screen and here.


Three that deserve more than a line

Has a kitchen ever been here? If a restaurant occupied the unit, the extraction, grease trap and power are probably already in. If not, creating them runs into tens of thousands and needs the building's agreement. The most expensive question this data answers — before you travel.

Is this a graveyard or a good street? A street that churns is not a street that dies: units can turn over and refill. And turnover only means something against its own trade, and against its own quartier — the same trade does not hold equally from one neighbourhood to the next. Compass measures both across three censuses.

Those figures are not printed here. They rest on the 2017 and 2020 vintages, whose licence has not been cleared, and the server withholds them from an anonymous caller. This page follows the same rule as the product: a rate derived from a withheld vintage is withheld too.

What did people actually pay? 25 661 goodwill sales published with their price since 2015. For the 5 971 tied to a single shopfront, the median Paris fonds changes hands between 160 000 and 170 000 € — a range, not a point, because goodwill prices are declared in round numbers: the median sits on a step and moves in jumps, so a single figure would be precise about something the source is not. The trade decides almost everything.

Food shopCafé / restaurantClothingPersonal services
250 000 €220 000 €86 000 €50 000 €

One address makes the point. At 10 rue Mandar, trace_premise returns six goodwill sales between 2017 and 2024, from 87 500 to 450 000 € — retrieved 7 October 2026. Each one is probable, not established: two shopfronts share that street number, and the notice does not say which was sold. The 2017 and 2020 census rows come back withheld, the 2023 one established.


How a number earns its place

Every figure arrives with its source, its licence, its date — and how sure it is.

mermaid
flowchart LR    A["APUR BDCom<br/>3 censuses"] --> M["Address<br/>matching"]    B["BODACC<br/>sales + insolvencies"] --> M    C["INSEE Sirene<br/>establishments"] --> M    M --> V{"Does the source<br/>name THIS unit?"}    V -->|"names it directly"| E["established"]    V -->|"two sources agree,<br/>neither names it"| F["corroborated"]    V -->|"address shared by<br/>several shopfronts"| G["probable"]    V -->|"source is silent"| H["undetermined"]    E --> O["Every figure carries<br/>source · licence · vintage · method"]    F --> O    G --> O    H --> O    O --> UI["Map and unit file"]    O --> MCP["MCP server,<br/>for an agent"]

Four levels, never a percentage. A confidence score out of 100 would be exactly the kind of unverifiable number this product refuses. The level is computed from columns that already exist, and every row carries the reason that produced it.

Composition across the corpus, measured 6 October 2026 — this is the quality metric, and improving means moving these four numbers leftward:

establishedcorroboratedprobableundetermined
51.2%5.9%37.0%5.9%

That 37.0% is structural, not laziness: BODACC names an address, BDCom names a unit, and 69% of units share their street number. No public data will say which of eight shopfronts was sold.

A gate runs the whole corpus against 56 invariants, 24 frozen baselines and 8 hand-verified chronologies before anything ships, and again every day on a schedule — invariants counted 6 October 2026 with grep -c '^-- @invariant ' eval/invariants.sql. Most of them check what the functions return; one checks what they are — a function exposing an observed column must be SECURITY DEFINER, because row-level security silently turns a withheld row into "never surveyed".

The badge above counts invariants; it does not say the gate passes. The reds currently open are the issues labelled porte-rouge.


Two founding constraints

Most commercial-property tools describe the unit — floor area, rent, photos — and leave you to infer the rest. Compass sells neither coverage nor granularity: it sells interpretation, and context is the product.

An interpretation is worth only what you can check. The tools in this market promise answers grounded in audited data — that names who verified. Compass promises figures re-derivable from a cited public source — that names who can verify: you. An internal audit is a promise. A cited source is a test anyone can rerun, including against us.

If a number cannot be re-derived from a cited public source, it is not shown.

No landlord declarations, no scraped listings, no proprietary estimate, no score invented to fill a gap. Missing data is displayed as missing — n/a, never 0.

If two units on the same street get the same verdict, Compass has said nothing.

The useful granularity is the street segment, sometimes the side of the pavement. An indicator that does not vary at that scale describes general context; it does not settle a decision.


Who it is for

The entrepreneur — the shopkeeper, restaurateur, craftsperson or franchisee who decides where to open. Once or twice in a working life, on a lease that binds for years.

An agent — an LLM asking the same question through an MCP server. Same scoring core, same traceability requirement, different output: JSON and a chain of thought instead of a map.

Not brokers. A broker qualifies dozens of locations a month and needs portfolios, bulk comparison, national coverage. Every one of those makes the product heavier for someone studying a single address in depth. Serving both serves neither — a broker who wants Compass gets what the agent gets: the API.


What it refuses

Every refusal buys something back. The trade is the point.

It refusesWhat that buys
A listings portalPosition upstream of the listing. Compass shows what is coming free — ceased trading, goodwill sold, court-wound-up, censused empty — not what everyone already sees
A rent estimateHonesty about the one number everybody wants. No open dataset of actual commercial rents exists in France
A revenue forecastCredibility. Inventing it would poison every other number on the page
A single score out of 100A bakery wants footfall, a yoga studio wants quiet, a wine merchant wants median income. One score averages away what pulls against itself
National coverageDepth. The sources that carry the value are local
An account to exploreNothing to get past before finding out whether the tool is any use
What it cannot answer, and why — the gaps shape the product more than the features do

What rent will I pay? No open observatory of commercial rents exists in France. Local rent observatories cover private housing; INSEE's ILC is a revision index, not a level. Street-level commercial values are sold by private vendors — which is the proof they are not open. Goodwill sale prices carry an indirect signal and nothing more.

How many people walk past this door? Paris has no permanent pedestrian sensor: the city's multimodal counters cover bikes, scooters, motorcycles, cars, lorries and buses — not pedestrians.

Vendors do sell the number, and "proprietary and expensive" is the weak objection — worth being precise about what it actually is. It comes from a panel of mobile handsets: SDKs embedded in third-party apps report GPS coordinates in the background, and the sample is then extrapolated by weighting it against known demographics. The vendors say so themselves — "We don't see everyone. We see a sample." Peer-reviewed work on a comparable panel measured a mean sampling rate of 7.5%, swinging between 4.5% and 14.5%, with low-income and less-educated populations under-represented and the urban/rural bias reversing sign mid-series.1

So the figure is modelled, never measured — and the buyer cannot see the panel size on their own street, cannot replay the weighting, and is not told when a recalibration moves last year's number. The objection is not honesty, it is verifiability. Compass measures presence and rhythm from open sources instead, and labels it a proxy on screen.

1 Li Z., Ning H., Jing F., Lessani M. N. (2024). Understanding the bias of mobile location data across spatial scales and over time. PLOS ONE 19(1):e0294430.

What do people here spend, and on what? Card transaction data: proprietary. No workaround.

Which units are on the market today? Commercial listings live on private portals whose terms forbid reuse. Which is why Compass works upstream of them instead.


Status

Honest labels, in the sense that built means the code runs and the gate passes — not that it is deployed.

ComponentState
Map, neighbourhood scoring, environment panelDemo — pre-recorded addresses in the 17th arrondissement, not yet wired to the ingested corpus
Provenance surfaced on every figureBuilt
BDCom ×3 · BODACC · Sirene · geographyBuilt — 85 418 units, 228 275 census records
Deployed to the hosted databaseLive since 15 August 2026 — read anonymously with the publishable key
Premise history in the browser — BDCom ×3 and BODACC on one timelineBuilt — demonstrated against the hosted database in a dev browser, not in the demo. docs/tickets/w0-fiche.md
Exportable one-address fileDesign, next up
MCP server for agentsPublished and listed — npx -y paris-compass-mcp (npm, MCP registry), six tools, anonymous read-only, nothing to configure.
Agent self-assessment of its own confidenceResearch

Where every number comes from

Connected today
SourceProducerUseLicence
OpenStreetMap (Overpass)OSM contributorsVacant and occupied units, retail, schools, healthcare, parks, transit, roadsODbL
Base Adresse NationaleEtalab / IGNGeocodingLicence Ouverte 2.0
Rent control datasetVille de Paris / OLAPHousing only — a catchment-area signal, never presented as a commercial rent, never multiplied by a floor area, never a filterODbL
CAMS Europe (Open-Meteo)CopernicusAQI, PM2.5, NO₂CC BY 4.0
GéorisquesBRGM / MTENatural and technological risks within 1 kmLicence Ouverte 2.0

Scores computed client-side: walkability, transport access, density per category, noise and footfall — the last two explicitly labelled estimates, for lack of a reliable open source.

Ingested in the hosted database, not yet in the demo
SourceProducerContribution
BDCom 2017 / 2020 / 2023APURDoor-to-door census of every ground-floor unit with a shop window, 224-activity nomenclature, floor-area bands. The unit identifier is stable across vintages, so three censuses give turnover measured against its own street, with previous lives as the evidence. Two limits are part of the claim: vacancy is measurable on 2017 and 2020 only — the 2023 layer carries retail alone, so a missing unit is "no longer a shop", not "empty" — and the licence differs by vintage, so BDCom cannot be announced as ODbL across the board
BODACCDILAGoodwill sales with their price, and insolvency proceedings — the closest public figure to what an entrepreneur will pay, and a signal that a unit is coming free
Sirene geolocatedINSEECorroboration: places an establishment of the same company at the address, which raises a notice to corroborated without ever making it established
PLU commercial protections (plub_protcom)Ville de ParisOn a protected linear, a ground-floor unit cannot change use — the first thing that can kill a project. Informational only, no regulatory value: the Portail des Règles d'Urbanisme is the authority. Version voted by the Conseil de Paris 20 November 2024
Planned
SourceProducerContribution
MobiliscopeCNRSPopulation actually present hour by hour — distinguishes an office district that triples at noon from a residential one
Transit validationsÎle-de-France MobilitésCounted entries per station, hourly since 2015 — replaces the footfall proxy with a measured number
DVFDGFiPSale prices of the walls per m²
INSEE IRIS / FiLoSoFiINSEEPopulation, income, socio-professional categories
GTFS IDFMÎle-de-France MobilitésReal travel times and frequencies
BruitparifBruitparifModelled and measured noise, replacing the road proxy
SitadelSDESPlanning permissions — future residents and future competitors, two years ahead

Scope

Paris intra-muros first, Île-de-France next. Depth over breadth: the sources that carry the value are local.


Stack

React 18 · TypeScript · Vite 5 · Tailwind + shadcn/ui · Leaflet (direct, no wrapper) · TanStack Query · Supabase + PostGIS

src/core/ is pure — no fetch, no React, no DOM. That is what lets the same scoring serve a browser, a test runner and an MCP server.

Run it locally

Node.js 18+.

sh
git clone https://github.com/IvandeMurard/paris-compass.gitcd paris-compassnpm installnpm run dev

Served at http://localhost:8080.

ScriptDoes
npm run devVite dev server with HMR
npm run typechecktsc --noEmit
npm run testVitest
npm run evalThe gate: invariants, baselines, golden cases
npm run buildProduction build

Open data sources need no key. For your own backend, put VITE_SUPABASE_URL and VITE_SUPABASE_PUBLISHABLE_KEY in .env.local. Only VITE_-prefixed variables reach the browser — never put a service-role or paid key there.


Licence and attribution

The code is Apache-2.0. The data is not.

That distinction matters more than it looks on a product built entirely from open data. The licence covers what is in this repository — the scoring core, the ingestion pipeline, the interface. It grants nothing over the datasets, which keep their own terms:

Requires
ODbL — OpenStreetMap, rent control dataset, BDCom 2023Attribution and share-alike. Any reuse must credit © OpenStreetMap contributors
Licence Ouverte 2.0 — Base Adresse Nationale, Géorisques, SireneNaming the source and its update date
CC BY 4.0 — CAMS Europe / CopernicusAttribution

BDCom 2017 and 2020 are not redistributable at all. Their licence differs from the 2023 vintage, which is why the database carries a publicly_redistributable flag per vintage and withholds their content from an anonymous caller — content and absence alike, so that withholding leaks nothing either.

This repository contains no data extract, and must not. It contains the code that fetches, models and cites the data.

Made by Ivan de Murard.

Interested in the approach, or in the MCP layer? Open an issue.

來源:README.md,提交 067c21f

工具

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版本歷史

3
  1. v0.1.4最新Oct 9, 2026
  2. v0.1.3Oct 7, 2026
  3. v0.1.2Sep 16, 2026

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