Housing Intel vs Onehome MCP
A side-by-side look at the Housing Intel and Onehome 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 Onehome 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 Onehome MCP when
- You need dedicated capabilities in the Real Estate domain.
- You prefer a local stdio subprocess transport.
- You have the keys it needs:
ONEHOME_TOKEN, ONEHOME_MAGIC_LINK. - You want tools like
onehome_get_user, onehome_get_groups, onehome_get_session_context.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Real Estate | Real Estate |
| Quality signal | 61/100 · Good | 63/100 · 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 | ONEHOME_TOKENONEHOME_MAGIC_LINK |
| Verified owner | Community listing | Community listing |
| GitHub stars | 1 | 1 |
| Directory activity | 1 views 0 installs 0 upvotes | 1 views 0 installs 0 upvotes |
| Tools | 10 | 21 |
| Full listing | View Housing Intel | View Onehome 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.
Onehome MCP tools 21
onehome_get_userReturns the OneHome user profile + the consumer-share groups attached. Share member e-mails and the agent's e-mail/phones are omitted unless `include_contacts: true`. For full agent / registered users, queries the GraphQL `user` endpoint. For magic-link consumer-share sessions (where `user { }` is access-denied), falls back to the data captured during the `checkToken` exchange — email, contact id, group/savedSearch ids, and the agent who shared with you.onehome_get_groupsList the OneHome groups your agent has shared with you. Share member e-mails and the agent's e-mail/phones are omitted unless `include_contacts: true`. For full agent / registered users, returns the GraphQL `user.groups` list. For magic-link consumer-share sessions (a single shared group), synthesizes a one-entry list from the `checkToken` session context.onehome_get_session_contextReturns one entry per registered session — its `session_id`, auth_mode, token expiry, and session scope (group_id / saved_search_id / agent_id / contact_id / mls_id) the MCP bootstrapped from each checkToken exchange. `active_session_id` flags which session answers by default; per-listing routing uses the active session when its `mls_id` matches the listing's `~MLS` suffix, else the one session that matches (several matches error — pick one with `onehome_set_active_session`). Tools default unspecified `group_id` / `saved_search_id` arguments from the active session's context, so this is the easiest way to see what they'll default to. Single-session use (the common case) returns a one-entry `sessions[]`.onehome_get_saved_searchFetch the agent-curated saved search by its id (UUID). Returns the search's name, filter criteria (`filters[]`), polygon, listing count, and the full list of OSK listing ids that compose the consumer share (`listing_ids`). Pass `include_listing_ids: false` to suppress the listing-id array if you only need the metadata. This is the canonical consumer-readable endpoint; the by-groupId variant is agent-only. `saved_search_id` defaults to the MCP's session context when omitted.onehome_get_saved_search_with_listingsCombo tool: the "show me my saved homes" flow in a single round trip. Internally runs `GetSavedSearchBySearchId` to fetch the saved search (name, filters, polygon, listingIds) and then `GetSavedListings` to inflate those listingIds into full property records — the same two-call sequence as calling `onehome_get_saved_search` followed by `onehome_search_properties(saved_search_id=...)`, but exposed as one tool so the magic-link-to-listings consumer flow is a single MCP call. Returns `{ saved_search, listings, count, page_info }`. Both `saved_search_id` and `group_id` default to the magic-link session context. Sort defaults to `property.MajorChangeTimestamp DESC` (Newest). Listings are returned via the GraphQL listing-card projection (`buildGetSavedListings`), which does NOT include `PublicRemarks` — so there is no raw `description` to opt back into here. Use `onehome_get_property(listing_id)` per row when you need the full description for a specific listing.onehome_search_propertiesFetch listings inside a OneHome consumer-share. Two modes: - With `saved_search_id`: fetch the agent-curated collection (the standard 'Homes at <name>' view). The MCP first resolves the saved search's listingIds and then inflates them via listingsBySavedSearchId — this is the only mode that works for non-agent consumer accounts. - With just `group_id` and no `saved_search_id`: try the raw `listings(groupId, browseParameter)` endpoint. If page 0 comes back empty with no reported results (the access-restricted shape consumer-shares hit) AND the session context has a `savedSearchId` for that same group, the tool falls back to the saved-search path and marks the response `fell_back_to_saved_search: true`. If there's no fallback target it raises a clear error rather than silently returning empty. An empty later page (paging past the end) is returned as an empty page, never swapped for the saved-search collection. Both args default from the MCP's bootstrapped session context (the magic-link checkToken response) when neither is passed explicitly. Sort is `MajorChangeTimestamp DESC` ('Newest') unless overridden. `include_dislikes: false` by default — flip it on to include listings you've thumbs-downed in OneHome. Listings here are returned via the GraphQL listing-card projection, which does NOT include `PublicRemarks` — so there is no `description` field on search results and no `include_description` flag to opt into one. Each listing carries the structured `extracted_features` object instead. Use `onehome_get_property(listing_id)` per row when you need the full description for a specific listing.onehome_search_suggestionsCross-feed suggestion search by address, MLS number, or partial query. Bypasses the group/saved-search structure and hits the global suggestion endpoint — useful for "find an address" or "look up by MLS number". Returns id, address parts, beds/baths, list price, thumbnail per match. Inflate any result with `onehome_get_property`. Optional `group_id` scopes suggestions to one OneHome market.onehome_get_propertyFetch full details for a single OneHome listing by id or portal URL. Returns address, list / close / previous price, $/sqft, beds/baths/sqft, lot size (raw `lot_size` {area, units} plus the derived `lot_size_acres` — null, never 0, for condos / lotless listings), year built, lat/lng, status, HOA fee, annual tax, virtual-tour URL, the primary photo, and an `extracted_features` block (lake_front, hot_tub, basement, furnished, dock, community) keyword-parsed from the description. The raw `description` (PublicRemarks) is omitted by default — pass `include_description: true` to keep it; in most cases the extracted features cover what callers need. OneHome scopes every listing to a group/market — `group_id` defaults to the magic-link session context; pass it explicitly only if you need to query a different group.onehome_get_property_photosFetch the full media gallery for a OneHome listing. Returns one entry per image with Thumbnail / Medium / Large CDN URLs, dimensions, the listing-room description (LongDescription), and display order. Pass either `listing_id` or a portal URL.onehome_compare_propertiesFetch 2 or more OneHome listings and align their facts side-by-side. Each target may supply `listing_id` (preferred) or `url` (a portal URL). Returns the full per-property record (with `extracted_features` populated) per row. Per-target errors are captured per-row — one bad target will not fail the whole call. Calls are concurrent. The raw `description` is omitted from each row by default (`include_description: true` to keep it). The redundant `summary` table is also opt-in via `include_summary: true` — by default only `rows[]` is returned, which already carries every fact.onehome_bulk_getFetch up to 200 OneHome listings in a single call. Returns one structured row per input id (no side-by-side summary table — use `onehome_compare_properties` for that). Each row is either `{ listing_id, status: "ok", property }` on success or `{ listing_id, status, error_kind, retryable, error }` on failure (`status` = `error_kind`: `timeout` / `bridge_down` / `pending` are retryable, `protocol` / `other` are real misses) — one bad id never fails the whole call. Calls fan out concurrently against `ListingById`, capped at 6 in flight to avoid swamping the bridge; transient timeouts are retried once per row before being captured as an error. The whole call is bounded by an overall deadline: any row still unsettled comes back `status: "pending"` with a top-level `pending` count — re-run just those ids. The envelope reports `count` / `ok` / `errored`. `extracted_features` is populated per row automatically. The raw `description` (PublicRemarks) is omitted by default — pass `include_description: true` to keep it. `group_id` defaults to the magic-link session context.onehome_get_schoolsFetch the Local-Logic school data for a coordinate — separate primary and high-school lists, each entry with name, attributes (types/grades/programs/levels), and proximity (walking distance + straight-line distance). Returns an `error` field with HTTP details if the consumer session does not have access (the schools endpoint is sometimes agent-only). lat/lng usually come from `onehome_get_property` (`latitude` / `longitude`).- +9 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"
]
}
}
}
Onehome MCP
{
"mcpServers": {
"onehome-mcp": {
"command": "npx",
"args": [
"-y",
"onehome-mcp"
],
"env": {
"ONEHOME_TOKEN": "YOUR_ONEHOME_TOKEN_HERE",
"ONEHOME_MAGIC_LINK": "YOUR_ONEHOME_MAGIC_LINK_HERE"
}
}
}
}
Frequently asked questions
Housing Intel is categorized under Real Estate and uses a local stdio subprocess. Onehome MCP belongs to Real Estate and uses a local stdio subprocess. Pick Housing Intel for real estate work and Onehome 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. Onehome 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 onehome-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. Onehome MCP has 63/100 (Good) with 1 views, 0 installs and 1 GitHub stars.