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grants_search

Read-onlyIdempotent

Search federal funding opportunities on Grants.gov (keyless). Filter by keyword, opportunity status (forecasted/posted/closed/archived), agency, funding category and eligibility. Returns opportunity number, title, agency, status, open/close dates and CFDA numbers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsNoMax results (default 25, max 100).
keywordNoFree-text keyword (e.g. 'clean energy', 'rural health').
agenciesNoAgency code filter (e.g. 'NSF', 'HHS'). Pipe-separate multiples.
oppStatusesNoPipe-separated statuses. Default 'forecasted|posted'. Options: forecasted, posted, closed, archived.
eligibilitiesNoApplicant-eligibility code filter (e.g. '25' state governments, '99' unrestricted). Pipe-separate multiples.
fundingCategoriesNoFunding category code filter (e.g. 'ENV', 'ED'). Pipe-separate multiples.
fundingInstrumentsNoFunding-instrument code filter (e.g. 'G' grant, 'CA' cooperative agreement). Pipe-separate multiples.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, non-destructive), so the bar is lower. The description adds genuine value beyond annotations by disclosing that the API is keyless and by enumerating the return fields (opportunity number, title, agency, status, open/close dates, CFDA numbers), which orients the agent on what results look like. No contradictions 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?

Two sentences with zero waste: first sentence states purpose and keyless access, second sentence enumerates filters and return fields. Everything earns its place, and the core action is front-loaded.

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?

For a read-only search tool with 7 optional parameters, the description covers the domain origin, filter capabilities, and return fields (partially compensating for the missing output schema). The only notable gap is the lack of an explicit pointer to grants_get_opportunity for fetching full opportunity details, which would complete the navigation story.

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% — all 7 parameters have meaningful schema descriptions including default values and pipe-separated syntax. The description summarizes these filters but adds no genuinely new semantics beyond what the schema already documents, so the baseline score of 3 applies.

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?

States a specific verb and resource ('Search federal funding opportunities on Grants.gov') plus the keyless qualifier, and lists concrete filter dimensions and return fields. This clearly positions it as the discovery tool and distinguishes it from the sibling grants_get_opportunity, which presumably retrieves a single opportunity's details.

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

Usage Guidelines3/5

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

The description establishes clear usage context — searching for funding opportunities with filters, and the keyless note signals no auth setup is needed. However, it never explicitly names the alternative (grants_get_opportunity) or states when not to use it, so the agent must infer the search-vs-detail split from sibling names alone.

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

B3.3/5.0
Disambiguation2/5

Several tool clusters overlap heavily—company due-diligence and risk tools (counterparty_risk_score, company_trust_check, entity_dossier, issuer_diligence_dossier, resolve_entity, entity_resolve), carrier vetting tools, sanctions screening tools, and recall tools all have subtle boundary distinctions. While descriptions are detailed, an agent navigating 294 tools will frequently struggle to pick the right one.

Naming Consistency3/5

Most tools follow a readable snake_case domain-prefix pattern (fdic_, edgar_, sanctions_, congress_), which helps. However, verb placement is inconsistent—search_available_datasets vs cdc_dataset_query, resolve_entity vs entity_resolve—and synonyms like search, lookup, get, detail, fetch, and status are used interchangeably.

Tool Count1/5

294 tools is an extreme number for a single MCP server, far beyond what an agent can reliably hold in context or select from accurately. The presence of tool-group discovery helpers mitigates but does not solve the fundamental scale problem.

Completeness4/5

The data breadth is genuinely extensive, covering finance, health, legal, real estate, transportation, energy, cyber, education, and many other domains, often with generic query fallbacks. Still, some capabilities are shallow or incomplete—package tracking stops at a link, property tools are demo-only in places, and caselaw coverage is limited—so it is not a fully complete surface.