HUD Housing Data
Server Details
Fair Market Rents, income limits, public housing, vouchers, and homeless counts
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.2/5 across 5 of 5 tools scored. Lowest: 3.6/5.
Each tool has a clearly distinct purpose targeting specific HUD data domains: fair market rents, homeless counts, housing vouchers, income limits, and public housing. The descriptions clearly differentiate what data each tool retrieves, with no overlap in functionality or ambiguity between tools.
All tools follow a consistent 'get_[data_type]' naming pattern using snake_case throughout. This predictable verb_noun structure makes it easy to understand what each tool does and maintains perfect consistency across the toolset.
Five tools is well-scoped for a HUD housing data server, covering major HUD program areas without being overwhelming. Each tool serves a distinct data domain that earns its place, making this an appropriately sized toolset for the server's purpose.
The toolset covers major HUD data domains well, including rental markets, homelessness, voucher programs, income eligibility, and public housing. Minor gaps might include data visualization/analysis tools or more granular filtering options, but the core data retrieval surface is comprehensive for the housing data domain.
Available Tools
5 toolsget_fair_market_rentsAInspect
Get HUD Fair Market Rent (FMR) values for 0-4 bedroom units.
Returns FMR data used to determine Housing Choice Voucher payment
standards and other HUD program parameters. Requires HUD User API
token; returns registration guidance if token is not configured.
Args:
state: Two-letter US state abbreviation (e.g. 'CA', 'WA').
county_fips: Optional 5-digit county FIPS code (e.g. '06037' for LA County).
If omitted, returns statewide FMR data.
year: FMR fiscal year (default 2024).| Name | Required | Description | Default |
|---|---|---|---|
| year | No | ||
| state | Yes | ||
| county_fips | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses critical auth requirement ('Requires HUD User API token') and failure mode behavior ('returns registration guidance if token is not configured') absent from annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with purpose upfront, followed by usage context, auth requirements, and parameter details; every sentence adds value beyond the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Comprehensive for a 3-parameter tool; covers auth, parameters, and purpose adequately given that output schema handles return value documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Fully compensates for 0% schema description coverage by providing detailed Args section with examples (e.g., '06037' for LA County) and behavioral notes (e.g., 'If omitted, returns statewide FMR data').
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb ('Get') + resource ('HUD Fair Market Rent values for 0-4 bedroom units') clearly distinguishes from sibling tools dealing with income limits, vouchers, and homeless data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage context ('used to determine Housing Choice Voucher payment standards') but lacks explicit when-to-use/when-not-to-use guidance versus siblings like get_income_limits.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_homeless_dataAInspect
Get Point-in-Time (PIT) homeless count data by Continuum of Care region.
Returns homeless population counts from the annual PIT count, broken
down by sheltered/unsheltered status and sub-populations. Data sourced
from HUD Exchange via ArcGIS open data. No API key required.
Args:
state: Two-letter US state abbreviation (e.g. 'CA', 'WA').
At least one of state or coc_code must be provided.
coc_code: Optional Continuum of Care code (e.g. 'WA-500', 'CA-600').
year: Optional year to filter results.| Name | Required | Description | Default |
|---|---|---|---|
| year | No | ||
| state | No | ||
| coc_code | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description discloses auth requirements ('No API key required'), data provenance ('HUD Exchange via ArcGIS'), and return structure ('sheltered/unsheltered status').
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Logical flow from purpose to return values to parameters; front-loaded with specific functionality; Args section efficiently delivers semantic details without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With output schema present, description appropriately focuses on input constraints (conditional requirement logic) and data source context rather than return value exposition.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Comprehensive compensation for 0% schema coverage: provides formats (two-letter state), examples ('CA', 'WA-500'), and validation rules (at least one required) for all three parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb ('Get') + specific resource ('Point-in-Time homeless count data') clearly distinguishes from sibling housing tools (rents, vouchers, income limits).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Documents critical constraint ('At least one of state or coc_code must be provided'), but lacks explicit guidance on when to use this vs sibling housing tools or when to prefer state vs coc_code filtering.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_housing_vouchersAInspect
Get Housing Choice Voucher (Section 8) program data by Public Housing Agency.
Returns information about voucher programs administered by PHAs in
the specified state, including total vouchers, utilization rates,
and spending. Queries HUD ArcGIS open data (no auth required).
Args:
state: Two-letter US state abbreviation (e.g. 'CA', 'NY').
limit: Maximum number of records to return (default 50, max 500).| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| state | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses data source (HUD ArcGIS), authentication requirements (none), and pagination constraints (default/max limits) despite no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with purpose front-loaded, followed by return value summary, data source note, and Args section; no redundant content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequately complete given output schema exists; mentions key return fields (utilization rates, spending) and auth, though could note rate limiting.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Fully compensates for 0% schema description coverage by providing formats, examples (e.g., 'CA', 'NY'), and constraints for both parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb ('Get') and resource ('Housing Choice Voucher/Section 8 program data') clearly distinguishes from sibling tools like get_public_housing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage through specificity of program type (Section 8), but lacks explicit when-to-use guidance or comparison to alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_income_limitsAInspect
Get HUD income limits (very low, low, median) by family size.
Returns income limit data used to determine eligibility for HUD
assisted housing programs. Requires HUD User API token.
Args:
state: Two-letter US state abbreviation (e.g. 'CA', 'NY').
county_fips: Optional 5-digit county FIPS code (e.g. '06037').
If omitted, returns data for all areas in the state.
year: Income limit fiscal year (default 2024).| Name | Required | Description | Default |
|---|---|---|---|
| year | No | ||
| state | Yes | ||
| county_fips | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses critical auth requirement (HUD User API token) not present in schema/annotations, though omits rate limits or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with front-loaded purpose (sentence 1), use case (sentence 2), auth (sentence 3), then detailed Args section with no wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Sufficient for tool complexity (3 simple params); leverages existence of output schema to avoid redundant return value documentation while noting 'by family size' output structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Comprehensive compensation for 0% schema description coverage with formats (2-letter state, 5-digit FIPS), examples, optionality behavior, and defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb+resource ('Get HUD income limits') with clear differentiators (very low/low/median by family size) distinguishing it from sibling rent/homeless/voucher tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
States the data is used for eligibility determination and requires API token, but lacks explicit when/when-not guidance compared to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_public_housingAInspect
Get public housing buildings and developments in a state.
Queries HUD's open ArcGIS data for public housing inventory.
No API key required. Returns building names, addresses, unit counts,
and managing Public Housing Agency information.
Args:
state: Two-letter US state abbreviation (e.g. 'WA', 'TX').
city: Optional city name to filter results.
limit: Maximum number of records to return (default 50, max 500).| Name | Required | Description | Default |
|---|---|---|---|
| city | No | ||
| limit | No | ||
| state | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Excellent coverage given no annotations: discloses data source (HUD ArcGIS), auth requirements (none), return values (names/addresses/unit counts), and constraints (default/max limits).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with summary, behavioral notes, and clearly delineated Args section; every sentence adds value beyond structured fields.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complete for tool complexity: covers data source, authentication, return structure, and parameter semantics, making it sufficient for invocation despite minimal schema metadata.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Compensates effectively for 0% schema description coverage by providing detailed Args section with format examples (e.g., 'WA', 'TX') and constraint explanations for all parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clear specific action (Get) and resource (public housing buildings/developments) that distinguishes from siblings dealing with rents, vouchers, or income limits.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use guidance or comparison against sibling tools like get_housing_vouchers or get_fair_market_rents.
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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