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mtgmon Mortgage Analytics MCP Server

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mtgmon Mortgage Analytics is answering right now. Last checked 11 min ago. It exposes 10 tools.

Read-only U.S. mortgage market, lender, GSE performance, and servicing analytics.

The linked repository no longer exists on GitHub — it was deleted or made private.

Uptime history 47 days of history
47 days agonow
100.0%
Uptime 24h
91 of 91 checks
10
Tools
read from the server
651 ms
Response time
average over 24h
open, no key
Access
streamable-http

What changed 20

Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 4 September 2026. No other catalogue keeps this.

7 Sep 10 tool descriptions were rewritten compare_lenders, get_dataset_status, get_hmda_product_analytics and 7 more
7 Sep 8 tools changed the parameters they ask for compare_lenders, get_hmda_product_analytics, get_lender_profile and 5 more
7 Sep a tool changed version
4 Sep a tool appeared get_hmda_product_analytics

This one has been quiet for a while

Quiet is not dead — but it is worth knowing when it wakes up, or when someone else takes it over. We watch the repository and tell you either way.

Three servers free · no card

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 11 min ago.

run in your terminal
claude mcp add mtgmon --transport http https://mtgmon.com/mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "mtgmon": {
      "url": "https://mtgmon.com/mcp"
    }
  }
}
~/.codex/config.toml
[mcp_servers.mtgmon]
url = "https://mtgmon.com/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "mtgmon": {
      "url": "https://mtgmon.com/mcp"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "mtgmon": {
      "url": "https://mtgmon.com/mcp"
    }
  }
}

Available tools 10

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

sec
get_sec_filing
Full detail for one SEC filing: metadata and EDGAR link, mtgmon's machine-generated summary, which tracked mortgage entities the filing concerns and in what role, named people with titles and compensation, extracted financial facts, and ownership rows. Get the filing_id from search_sec_filings first. Returns data.filing {filing_id, accession_number, filer_cik, form, filing_date, company_name, description, canonical_summary, summary_status, summary_model, edgar_url, ...}, data.associations [{display_name, ticker, cik, relationship_role, summary, link_status, ...}], data.people [{name, title, compensation, note}], data.financials [{metric, value, unit, period}], and data.ownership. Each list is capped. Verify summaries against the linked filing before relying on them. Behavior: read-only, no auth or API key, no PII, idempotent and safe to retry. The public endpoint https://mtgmon.com/mcp allows about 60 requests/min and 250 tool calls/day per client IP. Result shape is {data, meta}; meta carries available, as_of, source_scope, weighting, units, cache_status, caveats, and truncated. If meta.available is false the data is unavailable or the cache is still warming (retry after a few seconds); never report it as zero.
search_sec_filings
Search SEC EDGAR filings of mortgage-related public companies (lenders, servicers, mortgage REITs, insurers, GSEs) that mtgmon has summarized. Newest filing date first. Use for: finding a company's 10-K, 10-Q, 8-K, or other filings by ticker, CIK, form type, keyword, or date window, and getting the filing_id to pass to get_sec_filing. Do not use for: full filing text (only summaries are stored) or companies outside the mortgage sector. Returns data.filings (at most `limit` rows of {filing_id, accession_number, filer_cik, form, filing_date, company_name, description, summary_status, summary_excerpt, summary_created_at, edgar_url}) and data.next_cursor (pass back as `cursor` for the next page; null when exhausted; meta.truncated is true when more pages exist). Only filings whose summary processing finished are listed; summaries are machine-generated and should be checked against edgar_url. Behavior: read-only, no auth or API key, no PII, idempotent and safe to retry. The public endpoint https://mtgmon.com/mcp allows about 60 requests/min and 250 tool calls/day per client IP. Result shape is {data, meta}; meta carries available, as_of, source_scope, weighting, units, cache_status, caveats, and truncated. If meta.available is false the data is unavailable or the cache is still warming (retry after a few seconds); never report it as zero.
compare
compare_lenders
Side-by-side HMDA comparison of two lender groups: yearly volume, loans, rank, and market share for both; loan type / purpose / occupancy mix; and the top states with each lender's volume and the volume multiple between them. Requires canonical keys for both lenders: call search_lenders and pass each result's exact `name`. For a single lender use get_lender_profile. Returns data.lenders, data.current_year, data.previous_year, data.yearly (both lenders per HMDA year), data.loan_type_mix, data.loan_purpose_mix, data.occupancy_mix, and data.top_state_comparison (top_n rows with lender_1_volume, lender_2_volume, multiple). Volumes are USD; shares are percent. Behavior: read-only, no auth or API key, no PII, idempotent and safe to retry. The public endpoint https://mtgmon.com/mcp allows about 60 requests/min and 250 tool calls/day per client IP. Result shape is {data, meta}; meta carries available, as_of, source_scope, weighting, units, cache_status, caveats, and truncated. If meta.available is false the data is unavailable or the cache is still warming (retry after a few seconds); never report it as zero.
dataset
get_dataset_status
Coverage, freshness, and build metadata for every mtgmon dataset. No arguments. Use for: "how current is the data", finding the latest available month or HMDA year before quoting figures, or diagnosing another tool's meta.available=false. Returns data.datasets, a list of {name, description, category, provider, coverage, last_updated, last_updated_label, stats, refresh} covering GSE loan performance, HMDA, market rates, SEC filings, and derived marts; and data.build {app, lake, cache_backend, cache}. Refresh cadences differ by dataset; read each row's coverage and last_updated. Behavior: read-only, no auth or API key, no PII, idempotent and safe to retry. The public endpoint https://mtgmon.com/mcp allows about 60 requests/min and 250 tool calls/day per client IP. Result shape is {data, meta}; meta carries available, as_of, source_scope, weighting, units, cache_status, caveats, and truncated. If meta.available is false the data is unavailable or the cache is still warming (retry after a few seconds); never report it as zero.
hmda
get_hmda_product_analytics
HMDA origination counts, reported dollar amounts, averages, and year-over-year growth for one product family, optionally for one property state or one lender, with an annual history back to 2018. Use for: HELOC, reverse-mortgage, or closed-end mortgage origination volume and growth; product mix by loan program (conventional/FHA/VA/USDA), purpose, lien, occupancy, construction method, or business purpose; state-level or lender-level product questions. Do not use for: lender rankings or market share (search_lenders / get_lender_profile) or GSE loan performance (get_loan_performance). Important: product_family defaults to 'heloc'. Use 'closed_end_mortgage' for ordinary mortgages or 'all' for every HMDA origination. Source is the frozen annual FFIEC/CFPB HMDA Snapshot LAR (one release per year, 2018 onward); state filters use the property state, not the lender's headquarters. Returns data.selected_year, data.current and data.previous (each {year, origination_count, reported_amount_count, reported_amount_sum, average_reported_amount, reported_amount_max, origination_count_yoy_pct, reported_amount_sum_yoy_pct, average_reported_amount_yoy_pct}), data.history (one such row per year), data.filters (applied filters), data.definition, and data.source_releases. Amounts are USD; YoY fields are percent; for HELOCs the amount is credit available, not the drawn balance. Behavior: read-only, no auth or API key, no PII, idempotent and safe to retry. The public endpoint https://mtgmon.com/mcp allows about 60 requests/min and 250 tool calls/day per client IP. Result shape is {data, meta}; meta carries available, as_of, source_scope, weighting, units, cache_status, caveats, and truncated. If meta.available is false the data is unavailable or the cache is still warming (retry after a few seconds); never report it as zero.
lender
get_lender_profile
HMDA profile for one lender group: annual origination volume, loan counts, denial rate, national rank and market share, top states with market-share multiples, and loan type / purpose / occupancy / loan-size mix. Requires a canonical key: call search_lenders and pass the exact `name` (e.g. 'Rocket/Quicken'). Any other spelling returns meta.available=false with empty lists. Use compare_lenders for two lenders side by side. Returns data.lender_key, data.name, data.leis, data.current_year, data.previous_year, data.yearly (one row per HMDA year: originated_volume, originated_loans, purchased_volume, purchased_loans, denied_loans, applications_loans, total_funded_volume, avg_loan_size, denial_rate_pct, denial_rate_count_pct, rank, national_volume, market_share_pct), data.top_states {state, volume, loans, previous_volume, previous_loans} and data.state_market_multiples {state, lender_share_pct, market_share_pct, multiple, ...} (top_n rows each), data.loan_type_mix, data.loan_purpose_mix, data.occupancy_mix ({code, label, loans, volume}), and data.loan_size_histogram. Volumes are USD; shares and rates are percent. Behavior: read-only, no auth or API key, no PII, idempotent and safe to retry. The public endpoint https://mtgmon.com/mcp allows about 60 requests/min and 250 tool calls/day per client IP. Result shape is {data, meta}; meta carries available, as_of, source_scope, weighting, units, cache_status, caveats, and truncated. If meta.available is false the data is unavailable or the cache is still warming (retry after a few seconds); never report it as zero.
lenders
search_lenders
Find HMDA lenders and resolve names to canonical lender keys. Call this before any other lender tool. Use for: turning a company name ('Rocket', 'UWM', 'Wells Fargo', 'PennyMac') into its canonical key, ranking lenders by origination volume, or listing lenders by charter type or headquarters state. Then pass a result's exact `name` (e.g. 'Rocket/Quicken') as `lender` to get_lender_profile, get_hmda_product_analytics, or get_servicer_analytics mode='transfers', or as lender_a / lender_b to compare_lenders. Legal names such as 'Rocket Mortgage, LLC' are not keys and return meta.available=false downstream. Returns data.results (at most `limit` rows of {name, leis, charter_type, hq_state, recent_year, recent_volume, total_loans, volume_rank, subsidiary_count}), data.matched_count, and data.total_count. recent_volume is USD originations in recent_year (the latest HMDA year). Keys are holding-company or originator groups, so subsidiaries and LEIs roll up into one key. Behavior: read-only, no auth or API key, no PII, idempotent and safe to retry. The public endpoint https://mtgmon.com/mcp allows about 60 requests/min and 250 tool calls/day per client IP. Result shape is {data, meta}; meta carries available, as_of, source_scope, weighting, units, cache_status, caveats, and truncated. If meta.available is false the data is unavailable or the cache is still warming (retry after a few seconds); never report it as zero.
loan
get_loan_performance
Fannie Mae and Freddie Mac single-family loan-performance analytics for exactly one topic. Topics: - credit: monthly origination FICO and LTV (origination-UPB weighted). data.series {fico, ltv} and data.latest. - prepayment: monthly CPR and SMM (UPB weighted). - delinquency: monthly 30/60/90+ day delinquency rates (UPB-weighted stock rates). - loss: monthly loss severity (percent) and net loss (USD billions), plus data.latest_waterfall. - vintage: cumulative default-rate curves by vintage year over loan age (data.series = [{vintage, points}]). - transitions: loan-level monthly flows between Current/DQ30/DQ60/DQ90+/Modified/Liquidated (data.flows, top_n rows of {from, to, loans, upb, prob}) and data.history {cure_history, roll_30_60_history, roll_60_90_history}. - modification: outcomes at 6/12/18/24/36 months after a first 90+ DPD event, Modified vs NotModified arms (data.horizons, data.outcome_states, data.cohort_size, data.pooled, data.recent_vintages). - rate_sensitivity: modelled CPR under rate shocks (data.scenario = [{rate_shock_bps, predicted_cpr}], data.model {current_rate, current_cpr, slope}). - lock_in: active book by WAC vs today's mortgage rate: data.summary {total_upb, loan_count, wac_weighted, pct_below_mtg, pct_200bps_otm, pct_100bps_otm, pct_in_money} and data.largest_wac_age_cells {wac, age_band, upb}. Use for: agency credit quality, prepayment speeds, delinquency, roll and cure rates, modification outcomes, losses, the lock-in effect. Do not use for: originator volume or market share (search_lenders / get_lender_profile), today's rates (get_market_snapshot), per-servicer performance (get_servicer_analytics). Time-series topics return data.series {metric: [{date, value}, ...]} downsampled to max_points, plus data.latest. Scope is public GSE loan-level disclosures, not the whole U.S. market; meta.as_of is the latest reporting month. Behavior: read-only, no auth or API key, no PII, idempotent and safe to retry. The public endpoint https://mtgmon.com/mcp allows about 60 requests/min and 250 tool calls/day per client IP. Result shape is {data, meta}; meta carries available, as_of, source_scope, weighting, units, cache_status, caveats, and truncated. If meta.available is false the data is unavailable or the cache is still warming (retry after a few seconds); never report it as zero.
market
get_market_snapshot
Latest U.S. mortgage rates, TBA par coupons, Treasury and SOFR benchmarks, and mtgmon's fitted MBS basis in one call. No arguments. Use for: "what are mortgage rates today", 30y vs 15y, current coupon, 2y/10y Treasury, SOFR swap levels, whether MBS spreads are rich or cheap versus the model. Do not use for: rate history (not exposed here) or GSE loan performance (get_loan_performance). Returns data.rates, a list of up to 9 points {series, date, value, previous_value, change} for series MORTGAGE30US and MORTGAGE15US (Freddie Mac PMMS, weekly), tba_par_coupon_30y and tba_par_coupon_15y, 2Y and 10Y Treasury, and SOFR O/N, SOFR 2Y, SOFR 10Y; plus data.mbs_basis {model_version, latest_date, latest_basis_bps, latest_fair_bps, latest_gap_bps, latest_gap_zscore, r2_level_full_sample, ec_half_life_days, ...}. Rates are percent, basis is basis points. Series have different observation dates; quote each point's own date. Behavior: read-only, no auth or API key, no PII, idempotent and safe to retry. The public endpoint https://mtgmon.com/mcp allows about 60 requests/min and 250 tool calls/day per client IP. Result shape is {data, meta}; meta carries available, as_of, source_scope, weighting, units, cache_status, caveats, and truncated. If meta.available is false the data is unavailable or the cache is still warming (retry after a few seconds); never report it as zero.
servicer
get_servicer_analytics
Agency (Fannie Mae / Freddie Mac) servicer analytics in one of three modes. - mode='scorecard': largest servicers ranked by disclosed origination UPB for the current and previous year with average FICO and LTV. Returns data.servicers (top_n rows of {rank, name, volume, previous_volume, avg_fico, avg_ltv}), data.current_year, data.previous_year. - mode='performance': monthly CPR and 90+ day delinquency per top servicer for one origination vintage against the whole-book benchmark. Returns data.servicers {name: {cpr: [{date, value}], dq90: [...]}} downsampled to max_points, data.book {cpr, dq90}, data.vintage, data.latest_date. - mode='transfers': where one originator's Fannie Mae loans are serviced today and how servicing moved from the seller. Requires `lender` (canonical key from search_lenders). Returns data.seller_name, data.summary {loan_count, origination_upb, loans_with_transfer, pct_loans_with_transfer, total_transfer_events, ...}, data.latest_active_servicers {servicer, loans, upb, upb_share_pct}, data.top_routes and data.top_named_routes {from_servicer, to_servicer, events, event_share_pct}, data.first_to_latest {first_servicer, latest_servicer, loans, original_upb} (top_n rows each). Use for: "largest servicers", "which servicer prepays fastest or has the worst DQ for the 2021 vintage", "who services Rocket's loans now". Do not use for: HMDA origination volume (get_lender_profile) or book-wide delinquency (get_loan_performance topic='delinquency'). Coverage is disclosed agency loans matched by seller/servicer name, not any servicer's full portfolio. UPB and volume are USD; CPR and DQ90 are percent. Behavior: read-only, no auth or API key, no PII, idempotent and safe to retry. The public endpoint https://mtgmon.com/mcp allows about 60 requests/min and 250 tool calls/day per client IP. Result shape is {data, meta}; meta carries available, as_of, source_scope, weighting, units, cache_status, caveats, and truncated. If meta.available is false the data is unavailable or the cache is still warming (retry after a few seconds); never report it as zero.

Endpoints

URLTransportStateLatencyChecked
https://mtgmon.com/mcp streamable-http answering 645 ms 11 min ago

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mtgmon Mortgage Analytics — questions

Answers built from our own checks of this server.

What can mtgmon Mortgage Analytics do?
It exposes 10 tools, read directly from the server on our last check. Among them: compare_lenders, get_dataset_status, get_hmda_product_analytics, get_lender_profile, get_loan_performance, get_market_snapshot and 4 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
Is mtgmon Mortgage Analytics working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 651 ms. The bar chart above shows every period we have measured.
Is mtgmon Mortgage Analytics still maintained?
The linked repository no longer exists on GitHub — it was deleted or made private. We show this because it changes what you can expect: an unmaintained server may keep answering for months and then stop without warning.
How do I connect mtgmon Mortgage Analytics?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does mtgmon Mortgage Analytics need an API key?
No. mtgmon Mortgage Analytics completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 10 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is mtgmon Mortgage Analytics?
It answers our handshake in 651 ms on average, which is faster than 18% of all working MCP servers we measure. That is on the slow side — worth knowing if the tool sits inside an interactive loop. The comparison comes from our own checks across the whole registry, every 15 minutes.