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mtgmon Mortgage Analytics

Compare HMDA lenders

compare_lenders
Read-onlyIdempotent

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.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_nNoMaximum states in top_state_comparison, 1-50 (default 10).
lender_aYesFirst lender. Canonical HMDA lender key: the exact `name` value from a search_lenders result, e.g. 'Rocket/Quicken' or 'United Wholesale Mortgage'. Legal names such as 'Rocket Mortgage, LLC' do not match and return meta.available=false.
lender_bYesSecond lender, different from lender_a. Canonical HMDA lender key: the exact `name` value from a search_lenders result, e.g. 'Rocket/Quicken' or 'United Wholesale Mortgage'. Legal names such as 'Rocket Mortgage, LLC' do not match and return meta.available=false.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
metaYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / lender_a / description
      Added value: +"First lender. Canonical HMDA lender key: the exact `name` value from a search_lenders result, e.g. 'Rocket/Quicken' or 'United Wholesale Mortgage'. Legal names such as 'Rocket Mortgage, LLC' do not match and return meta.available=false."
    • addedInput schema / properties / lender_b / description
      Added value: +"Second lender, different from lender_a. Canonical HMDA lender key: the exact `name` value from a search_lenders result, e.g. 'Rocket/Quicken' or 'United Wholesale Mortgage'. Legal names such as 'Rocket Mortgage, LLC' do not match and return meta.available=false."
    • addedInput schema / properties / top_n / description
      Added value: +"Maximum states in top_state_comparison, 1-50 (default 10)."
  2. First observed

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description goes beyond the annotations by detailing read-only, idempotent, no-auth, no-PII behavior, rate limits, and the meta.available flag including cache-warming retry instructions. This fully discloses behavior without contradicting the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is comprehensive but slightly redundant in the 'Returns' list, which repeats the same fields in a paragraph and bullet-like form. However, the structure is logical and front-loaded with purpose, making it efficient for an agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity, the description covers all necessary context: input requirements, output structure, meta fields, error conditions (unavailable, cache warm), and rate limits. No critical operational detail is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All three parameters have thorough descriptions in the schema (top_n bounds, lender_a/b canonical key requirements with examples). The description augments the schema by explaining why legal names fail and how to resolve them, exceeding the baseline coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs a side-by-side comparison of two lender groups across multiple dimensions (volume, loans, rank, market share, loan type/purpose/occupancy mix, top states). This distinguishes it from siblings like get_lender_profile (single lender) and search_lenders (search).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly instructs users to call search_lenders first to obtain canonical keys and pass exact `name` values. Also notes that for a single lender, get_lender_profile should be used instead, providing clear alternation guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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