Free joined public records for small business and CRE: Twin Cities parcels, sales, licences
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β we're steadily working through the catalog.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
A free, open source MCP server that teaches any AI how to research a small business β and, more usefully, where the public records actually are.
Nine of its tools ship methodology, not data. Each returns a rigorously structured framework β a research procedure, an output schema, a quality rubric, the traps β and the calling model executes the research itself, with its own tools and its own keys. Those nine call nothing at all.
Two ship the records. twin_cities_datasets and twin_cities_records answer
from joined public records for the seven-county Minneapolis-St. Paul metro β
parcels and lot lines, recorded sale prices, owners, rental licences,
contamination files, business counts by trade, census tracts. Ask about one
address and they answer about that address. They call
brickandmortar.dev/api/export, which we
run; no tool here calls any third party. Every answer is a true row count, at
most six example rows, and a link to the complete file β never a file inline.
See /privacy for exactly what those two transmit and what is kept.
That split is deliberate and dated: the server was built on "no remote calls to our servers" (2026-08-16), which rested on a thesis retired the next day β the join is the moat, and the data ships. Confirmed 2026-08-20; the nine are untouched.
Live endpoint: https://brickandmortar.dev/mcp
No auth, no account, no key. Add it as a custom connector and ask.
A capable model already knows how to reason about a small business. What it does not know is the operational trivia that lives in nobody's training data:
Touches predicate returns zero touching parcels rather than
an error, so adjacency quietly becomes "this parcel touches nothing";Every one of those produces a plausible wrong answer rather than a failure. That is the whole problem with public data, and it is what this server is for.
The frameworks are the reasoning. src/tools/sources.ts
is the map β where each record lives, how to reach it, and the specific way it
lies. Every access pattern and trap in it was measured live against the agency's
own endpoint while building a real two-metro property and review corpus, not
recalled from training data.
Start with data_source_atlas. It is the one that changes what the rest are worth.
| Tool | What it does |
|---|---|
data_source_atlas | Given a real question and a place, returns a source-first research plan: which public record settles it, how to reach it, and what the public record cannot answer at all. Handles the jurisdictional fork (does this state even record sale prices?) before anything else. |
business_teardown | Full structured teardown of one named business β presence, review signal, competitive position, pricing posture, visibility gaps, prioritized evidence-cited recommendations. |
competitor_landscape | Maps the local competitive set: true competitors vs. adjacent players, positioning matrix, saturation signals β corroborated against an administrative establishment count, not just map results. |
review_intelligence | Mines public reviews: complaint taxonomy, theme extraction, sentiment trajectory, red flags for buyers. Rates, never raw counts. |
local_visibility_audit | Local search presence audit: map-pack factors, listing consistency, category selection, site fundamentals β a scored checklist. |
pricing_benchmark | A defensible local pricing comparison, including how to normalize across bundles and what to do when nobody publishes prices. |
broker_diligence_prep | Pre-diligence for brokers and buyers: SDE framing, multiple ranges, red-flag checklist, seller questions β plus the county's own record on the real property. |
market_opportunity_scan | Gap analysis for a category Γ metro: underserved demand vs. a spot that is empty for a reason. |
compose_report | Assembles prior tool outputs into one client-ready report, matched to the audience. |
twin_cities_datasets | What joined public records we publish for the seven-county MinneapolisβSt. Paul metro: row counts, columns, the cuts available, the counties each actually covers. |
twin_cities_records | Asks those records a question β one property or the whole market. Returns the true matching row count, six example rows, and a link to the complete file. |
request_a_feature | The only tool here that sends rather than answers. Files a feature request, a data request or a correction to the person who builds this, when the server falls short of what the user wanted. |
Stated plainly, because the boundary is the design:
request_a_feature posts the request you dictated to us and nowhere else.Add the endpoint as a custom connector in Claude, or any MCP-compatible client:
Then ask something real:
"Where would I actually find what 1420 Grand Ave in Saint Paul last sold for?"
"I want to know if Wichita has room for another dog daycare β what should I pull?"
"Run a business_teardown on Mucci's Italian in Saint Paul, MN."
wrangler dev runs against Miniflare's local KV simulation, so the usage ledger
works out of the box with no Cloudflare account needed.
Or drop --cli for the interactive web UI (npm run inspector). Every tool
should list with an outputSchema, and a tools/call against each should return
structuredContent matching it, with no isError. All of them list with
readOnlyHint: true except request_a_feature, which sends a message and says
so.
Ships to the free *.workers.dev subdomain β no DNS work, no paid plan.
tools/list is ~43 KB (~10.8K tokens) and sits in the client's context for the
whole session whether or not a tool is ever called. Most of that is the shared
outputSchema serialised once per tool. If you fork this and add tools, read the
comment at the top of src/tools/types.ts first β every
.describe() in that schema is paid for once per tool, forever.
Architecture and the SDK/transport decision: ARCHITECTURE.md.
The most valuable contribution is a measured trap. If you pull a public
source and it lies to you in a way that returns a plausible number instead of an
error, that belongs in sources.ts β with how you measured it and when. Access
patterns rot as agencies reorganise; a correction with a date on it is worth more
than a new framework.
Please don't add anything that makes the server call an external service. The no-outbound-calls property is what makes it free to run and safe to trust.
Built by Brick & Mortar β a small team in Saint Paul that maintains real local-market corpora (county parcel records, recorded sales, review panels, federal series) for its own products. The frameworks here are what we learned building those, including the traps that silently return a plausible wrong number.
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