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usaspending-mcp-server

Search Award Recipients

usaspending_search_recipients
Read-onlyIdempotent

Search for organizations or individuals receiving federal funds by name, UEI (Unique Entity Identifier), or DUNS. Returns recipient hash IDs, UEI/DUNS identifiers, total award amounts, and hierarchy level. Results are paginated — use page to retrieve matches beyond the first page; page_metadata.total reports the full match count. Recipient hash IDs from this tool can be passed to usaspending_get_recipient for full profiles. Recipient level: P = parent organization, C = child entity, R = standalone.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number (1-based) — request the next page to retrieve matches beyond the first
limitNoMaximum results per page (1–100)
keywordYesName, UEI, DUNS, or keyword to search for — partial matches are supported
award_typeNoFilter by award type category to scope the total amounts returned

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoCurrent page number returned
errorNoPresent when the call failed. Absent on success.
noticeNoRecovery hint — how to continue to the next page when more results exist, or how to broaden the search when empty. Absent when the full match set fits on this page.
resultsNoMatching recipients
has_nextNoWhether there are more pages of results
totalCountNoTotal matching recipients across all pages
page_metadataNoPagination metadata — page through with the page input to reach later matches
recipient_countNoNumber of matching recipients returned on this page

TDQS

A4.2/5.0
Behavior4/5

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

Annotations provide readOnlyHint and idempotentHint, so the safety profile is known. The description adds behavioral nuance beyond annotations: pagination mechanics (use page, page_metadata.total), return fields, and hierarchy level definitions (P, C, R). No contradiction with annotations.

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

Conciseness5/5

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

The description is compact and front-loaded. Each sentence serves a purpose: core search action, returned fields, pagination, and hierarchical level explanation. No wasted words; ideal length for an agent to quickly parse.

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

Completeness4/5

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

Given the presence of an output schema (which covers return values), the description covers essential aspects: what to search, pagination behavior, and hierarchy codes. It also references the companion tool. Minor gaps like error handling or rate limits are not documented, but they are not required given the annotations and output schema. Complete for typical agent use.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all parameters. The description adds marginal semantics (e.g., 'partial matches are supported' is already in schema; pagination note aligns with page parameter but is more behavioral). No new parameter-level meaning is provided beyond the schema.

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?

Clear verb+resource: 'Search for organizations or individuals receiving federal funds' by name, UEI, or DUNS. It distinguishes itself from siblings like usaspending_get_recipient by explicitly noting returned hash IDs feed into that tool. Purpose is specific and unambiguous.

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

Usage Guidelines4/5

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

States clear context: search for recipients by identifier and that results are paginated. Mentions companion usaspending_get_recipient for full profiles, implying a follow-up path. However, it doesn't explicitly state when NOT to use this tool or compare with other search siblings (e.g., usaspending_search_awards), so not a full 5.

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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TDQS

A4.3/5.0
Disambiguation5/5

Each tool targets a distinct entity or operation: agency, award, subaward, transaction, federal account, recipient, and various spending breakdowns. Even similar-sounding tools like get_award_federal_accounts vs get_federal_account are clearly separated by their core purpose (award funding sources vs account budget details).

Naming Consistency4/5

Almost all tools follow the usaspending_<verb>_<object> pattern (e.g., get_award, search_recipients). The spending_* series breaks the verb-noun convention but is internally consistent. Minor deviation lowers the score slightly.

Tool Count4/5

At 18 tools, this is on the higher end of reasonable but each tool maps to a distinct USAspending API endpoint and covers a different aspect of federal spending. The count is justified by the breadth of the domain, though it feels slightly heavy.

Completeness5/5

The surface covers award search/detail, agency navigation, federal accounts, recipients, subawards, transactions, IDVs, and multiple spending aggregations (category, geography, time, disaster). No obvious dead ends: all ID-producing tools have corresponding lookup tools, and common workflows like award→federal account→breakdown are fully supported.