Housing Intel vs Redfin MCP
A side-by-side look at the Housing Intel and Redfin MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Housing Intel for real estate work as a local process; choose Redfin MCP for real estate as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Housing Intel when
- You need dedicated capabilities in the Real Estate domain.
- You prefer a local stdio subprocess transport.
- You want tools like
case_shiller_metro_compare, housing_market_snapshot, housing_property_report.
Choose Redfin MCP when
- You need dedicated capabilities in the Real Estate domain.
- You prefer a local stdio subprocess transport.
- You want tools like
redfin_search_properties, redfin_sweep_area, redfin_get_property.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Real Estate | Real Estate |
| Quality signal | 61/100 · Good | 64/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | Not declared |
| Pricing | Not declared | Not declared |
| Required env vars | None listed | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 1 | 3 |
| Directory activity | 1 views 0 installs 0 upvotes | 1 views 0 installs 0 upvotes |
| Tools | 10 | 22 |
| Full listing | View Housing Intel | View Redfin MCP |
Tools & capabilities
Housing Intel tools 10
case_shiller_metro_compareCompare Case-Shiller home price indices across multiple US metros in one call (the 20-city composite). For each metro returns latest level, 3-month change, 12-month change, all-time peak, drawdown from peak, and a softening flag. Output also ranks metros softest → strongest. Use for "which metros are softening", "Case-Shiller for [list of cities]", "compare housing prices in X, Y, Z" queries — picks the right per-metro FRED series IDs (DNXRSA, PHXRSA, TPXRSA, etc.) so callers don't have to. Available metros: Atlanta, Boston, Charlotte, Chicago, Cleveland, Dallas, Denver, Detroit, Las Vegas, Los Angeles, Miami, Minneapolis, New York, Phoenix, Portland, San Diego, San Francisco, Seattle, Tampa, Washington DC. NOT A CURRENT-MARKET READ: Case-Shiller is monthly, published on a roughly two-month lag, and each value is a three-month moving average — so the newest observation is typically 90-120 days old and describes a trailing quarter. The `freshness` block states the exact age of the call you made.housing_market_snapshotGet national housing market overview: mortgage rates, housing starts, Case-Shiller index, unemployment, construction employment. Optionally add metro-level prices (e.g., "Denver", "Atlanta"). For comparing Case-Shiller across multiple metros use case_shiller_metro_compare instead. THE COMPONENTS DO NOT SHARE A DATE — they are weekly, monthly and quarterly official statistics, each published on its own lag, so one call can span months of vintages. `freshness` states the span in days and names the oldest component; read it before comparing components against each other.housing_property_reportAnalyze a property by address and zip code. Returns valuation estimate, sales history, tax assessment, and detailed characteristics.housing_rental_analysisEvaluate rental investment potential by address and zip code. Returns estimated rent, fair market rents, and CPI rent trends.housing_affordability_checkCheck housing affordability in a market. Returns mortgage rate, median price, monthly payment, required income, and HUD limits. Optionally specify metro (e.g., "Denver"). The inputs are official statistics on DIFFERENT cadences — a weekly mortgage rate against a quarterly median price — so the monthly payment is an illustrative ratio of published figures, not a live quote. `freshness` states the span and the age of each input.housing_employment_outlookAssess labor market health for housing demand. Returns employment, construction jobs, residential building employment, unemployment rate, and job openings. All BLS monthly releases; each series carries its own `observation_date` and `cadence` (JOLTS runs an extra month behind CES/LAUS), and `freshness` states the span. `snapshot_date` is the call date, not the data date.housing_signal_scanScan 45+ housing indicators for anomalies and reversals. Flags unusual moves across rates, starts, sales, prices, wages, unemployment, and rent. Each signal carries its own `observation_date` and `cadence` — series here span weekly (mortgage rate) to quarterly (median sales price), and Case-Shiller is additionally a 3-month moving average, so "turned negative" does not mean "this month" for every series. `freshness` states the full span and the oldest component.housing_mortgage_historyFreddie Mac Primary Mortgage Market Survey — the weekly US mortgage INTEREST rate (the annual percentage borrowers pay on a home loan, e.g. 6.5%), back to 1971. This is the borrowing cost paid by home buyers. Returns the latest snapshot, a time series for the requested window, and min/max/avg stats. Sourced from Freddie Mac directly (not FRED), ingested weekly by the Pipeworx data pipeline.housing_market_screenRank US metros for rental cash flow in ONE call — the "which markets are best for a landlord" view. Returns metros sorted by gross rent yield = (Zillow median monthly rent × 12) ÷ Zillow typical home value. No per-metro orchestration and no API key. Use for "best/worst rental markets", "highest-yield metros", "where does rent go furthest vs. home prices". Tune with direction (top = highest yield / best cash flow, bottom = lowest), limit, and optional home-value bounds. rent_as_of and home_value_as_of are two independent Zillow queries and can land on different months; `freshness` says whether they matched this call.housing_metro_demandDemand + rent-durability signals for a shortlist of US metros in ONE call — population & 5-year growth, renter share, median household income, and unemployment, straight from Census ACS. Deterministic by metro (CBSA-keyed) — NO FRED series-ID guessing. Pass `metros` ("City, ST", e.g. the top results from housing_market_screen). This is the Stage-2 "is the demand real?" filter on a yield shortlist — high yield in a shrinking metro is a trap. No API key needed. HIGHEST-LAG SOURCE IN THIS PACK: figures are a Census ACS 5-YEAR rolling average (currently 2018-2022, released Dec 2023) — for structural demand, not a current-quarter read. `freshness` states the exact age.
Redfin MCP tools 22
redfin_search_propertiesSearch Redfin listings by location (city, ZIP, neighborhood, or full street address) and optional filters. Resolves the location via Redfin's autocomplete then queries the gis API; full street addresses short-circuit to the single matched home (no gis call). Returns matching properties with price, beds/baths, sqft, year built, address, and the Redfin home URL. `resolved_as` is `'region'` / `'address'`. `coverage` is `'full'` (gis indexed this region), `'profile_only'` (Redfin has profiles for individual addresses here but search isn't indexed — use redfin_get_by_address per property), or `'none'`. `result_cap_hit: true` signals the result page is full — gis returned as many rows as requested (`limit`, default 40, max 350) — so more listings likely exist; raise `limit` or narrow with price/beds filters. ZIP queries that fall into Redfin's cross-continent fallback (e.g. ZIP 28746 returning Seattle results) now error loudly. Only `for_sale` status is supported; `sold` / `for_rent` return an error (use redfin_get_comparable_rentals for rentals, redfin_get_market_report for sold-price trends). Read-only; safe to call repeatedly.redfin_sweep_areaEnumerate EVERY for-sale Redfin listing inside a bounding box without silent truncation. Redfin's gis API returns at most 350 homes per call and ignores server-side filters, so this tool searches drawn-map polygons, recursively quarters any tile that hits the cap, dedupes by property_id and re-applies the caller's filters locally. Homes outside the box and tiles where Redfin drifted to another region are left out. Alternatively pass `zips` (ZIP mode) to sweep a list of ZIP regions instead of map tiles, when Redfin ignores drawn-map polygons. Returns a completeness summary (requests, tiles or ZIPs, unique listings, tiles/ZIPs still at the cap, drift warnings) plus the listings inline by default; pass the optional `output_path` to write them to a new JSON file instead, for large areas (inside the output directory: REDFIN_OUTPUT_DIR, default ~/Downloads/redfin-mcp). Sequential requests with a delay. Read-only against Redfin; the only write is the optional local output file.redfin_get_propertyFetch a property's full Redfin record. Provide one of: (a) `url` — full Redfin homedetails URL or path, resolved via the initialInfo endpoint; (b) `property_id` alone — resolved internally by following Redfin's /home/<id> redirect to the canonical listing, then initialInfo; or (c) `property_id` + `listing_id` — fastest, skips resolution and goes straight to aboveTheFold. Returns address, beds/baths, sqft, lot_size (sq ft), year built, price, status, days on market, plus derived fields (lot_size_acres, price_drop_*, hoa_monthly_usd, last_sold_*, tax_annual, extracted_features). lot_size / lot_size_acres are null (never 0) for condos and listings with no public-records lot. `primary_photo_url` is a raw Redfin CDN URL and is dropped on the default `compact` view — pass `view: "full"` for it, or use `redfin_get_property_photos` for the whole gallery. The raw marketing description is OMITTED by default — opt in with `include_description: true`. Set `include_price_history: true` to bundle the full price history (and the cross-MCP-normalized `events_normalized` view) inline; set `include_tax_history: true` for `tax_history`. Read-only; safe to call repeatedly.redfin_get_saved_homesThe signed-in user's favorited homes on redfin.com. Returns `{ count, homes }` — each home has address, price, beds/baths, status — plus a `note` when none were found (no favorites vs. a page-scrape miss). Requires the user to be signed in. Read-only; safe to call repeatedly.redfin_get_saved_searchesThe signed-in user's saved searches on redfin.com, derived from the saved-searches page HTML. Returns `{ count, searches }`; each entry is `{ url, region_segment, display_text }`. Requires the user to be signed in. When none are found, `searches` is empty and a `note` explains it may be no saved searches or a page-scrape miss. Read-only; safe to call repeatedly.redfin_get_market_reportMarket report for a Redfin region: median list/sold prices, $/sqft, sale-to-list ratio, total homes for sale + sold, all with year-over-year and month-over-month change. Provide either (a) `location` — free-text we resolve via autocomplete (best with city names; "New York", "Seattle"; neighborhoods typically return empty data), or (b) `region_id` + `region_type` directly. `property_type` defaults to 1 (all). Each metric returns `{ label, value, unit, yoy_change_fraction, yoy_direction, mom_change_fraction, mom_direction }`. Read-only; safe to call repeatedly.redfin_calculate_mortgageLocal-only mortgage payment calculator. Returns a full PITI breakdown (principal + interest, property tax, insurance, HOA, PMI) and total interest over the life of the loan. No network call — fully deterministic, safe to use for scenario comparison without burning a fetch. Provide either `down_payment` OR `down_payment_percent`; defaults to 20%. Property tax can be given as `property_tax_annual` or `property_tax_rate` (% of home price). PMI applies automatically when LTV > 80% and `pmi_rate` is provided.redfin_get_price_historyListing-price events for a property — listings, price changes, pending, sold, etc. Each entry has a date, event description, price, days-on-market at that point, and the data-source attribution (MLS, county records, etc.). Also returns the tax-history series from public records. Provide either `url` or `property_id`+`listing_id`. Read-only; safe to call repeatedly.redfin_compare_propertiesFetch and compare 2 to 25 Redfin properties side-by-side. Provide an array of targets, each either a `url` or a `property_id`+`listing_id` pair. Returns the full per-property record (price, beds/baths, sqft, year built, HOA monthly, last sold, derived price-drop, etc.). For >25 properties or workflows that don't need side-by-side analysis use `redfin_bulk_get`. Pass `include_summary: true` for an aligned-by-field `summary` table (default false to save context — the per-row records carry the same data, so emitting both duplicates ~30% of the response weight). Each record's `extracted_features` (lake_front, hot_tub, basement, furnished, dock, community) is always included. The raw marketing description is omitted by default — opt in with `include_description: true`. Errors for individual properties are captured per-row with a `status` (`ok` / `timeout` / `bridge_down` / `protocol` / `pending` / `other`) and `retryable`. Server-side concurrency (~6 in flight) with retry-once-on-timeout per row; the whole call is bounded by an overall deadline, and any row still unsettled then comes back as `status: "pending"` (retryable) with a `pending` count.redfin_get_climate_riskFirst Street Foundation climate risk scores for a property. COVERS: flood (factor 1–10, FEMA zones, 30-year annual chance series), fire (factor 1–10, relative risk, insurance price band, provider count), heat (factor 1–10, cumulative-risk projections at 0/5/10/15/20-year horizons). DOES NOT COVER: landslide. This is the Helene-relevant risk vector in the NC mountains market and many parts of California / the Pacific Northwest. First Street has no landslide product — for that vector check the NC Geological Survey landslide hazard maps (NC-specific) or USGS landslide hazard data (national). Surfaced on every response as `not_covered: ['landslide']`. Response shape: when First Street data is available, `available: true` with the risk blocks; when not, `{ available: false, reason }` where reason is one of `no_first_street_data`, `new_construction`, `address_outside_coverage`. Sourced from Redfin's server-rendered homedetails HTML (no clean stingray endpoint exists). Pass a homedetails URL (full or path) — it must end in a `/home/<propertyId>` segment; any other page is rejected without being fetched. When a `cluster_id` is surfaced, properties with the same value typically share identical climate scores — use that to group N properties and skip redundant fetches.redfin_get_climate_risk_bulkFetch climate risk for up to 100 property URLs in a single call. Same per-property shape as `redfin_get_climate_risk`; output preserves input order. Per-row error capture — properties without First Street data return `{ available: false, reason }` without aborting the batch. Server-side concurrency (~5 fetches in flight) with retry-once-on-timeout per URL. The whole call is bounded by an overall deadline: any URL still unsettled then comes back as `status: "pending"` (retryable) with a `pending` count, so re-run just those. Use this when batching ~60-property workflows where climate risk is the dominant cost. Limitations from the per-property tool apply (no landslide coverage).redfin_get_area_climate_baselineFetch climate risk for a small set of representative URLs in an area, then return their averaged baseline values plus the shared cluster_id when present. Use this as a cheap area-level read BEFORE fanning out a per-property call: if all sample properties agree (same cluster_id, same fire/flood/heat factors), the baseline applies to the whole cluster and N redundant fetches are avoidable. Pass 2–10 URLs you believe represent the area; returns the aggregate plus the per-URL responses for transparency. Server-side concurrency (~5 fetches in flight) with retry-once-on-timeout per URL; the whole call is bounded by an overall deadline, and any sample still unsettled then comes back as `status: "pending"` (retryable) with a `pending` count and is left out of the averages. Limitations of the per-property tool apply (no landslide coverage — note documented in the per-property tool description).- +10 more on the listing page
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Housing Intel
{
"mcpServers": {
"housing-intel": {
"command": "npx",
"args": [
"-y",
"@pipeworx/mcp-housing-intel"
]
}
}
}
Redfin MCP
{
"mcpServers": {
"redfin-mcp": {
"command": "npx",
"args": [
"-y",
"redfin-mcp"
]
}
}
}
Frequently asked questions
Housing Intel is categorized under Real Estate and uses a local stdio subprocess. Redfin MCP belongs to Real Estate and uses a local stdio subprocess. Pick Housing Intel for real estate work and Redfin MCP for real estate.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Housing Intel has no declared pricing — check the project's own site. Redfin MCP has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add housing-intel and redfin-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Housing Intel has a quality signal of 61/100 (Good) with 1 views, 0 installs and 1 GitHub stars. Redfin MCP has 64/100 (Good) with 1 views, 0 installs and 3 GitHub stars.