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Federal Grants — find funding you are actually eligible for

by io.github.wyattpalm2-eng

find_federal_grants

Find open U.S. federal grant opportunities an organization is ACTUALLY eligible to apply for. Filters by the machine-readable applicant-type code Grants.gov publishes on every opportunity, so ineligible opportunities are excluded rather than ranked low. Returns deadlines, award ceilings, cost-sharing requirements, and what prior winners of the same program actually received. Free, no key, live federal data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax opportunities to return (default 10).
keywordNoMission or topic, e.g. 'housing', 'mental health', 'workforce'. Broad single terms return more.
organizationTypeYesThe federal applicant category the organization files under, e.g. nonprofit_501c3, small_business, tribal_government, school_district.
includeForecastedNoInclude opportunities announced but not yet open — useful for preparing early.

Schema Changelog

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

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses that data is free, requires no key, is live, and uses machine-readable applicant-type codes. It also states what is returned (deadlines, ceilings, cost-sharing, prior winner amounts), adding useful behavioral context beyond the schema.

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 three sentences, front-loaded with the primary value, and every clause adds information. It avoids repetition and is highly scannable.

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?

The tool has four parameters and no output schema, but the description covers key output elements (deadlines, awards, cost-sharing) and the filtering logic. It doesn't fully describe the response format or edge cases like zero results, but the description is strong enough for a search tool.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds context by explaining how organizationType maps to Grants.gov's applicant-type code, how keyword affects results (broad terms return more), and the purpose of includeForecasted. This enhances understanding 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?

The description clearly states the tool finds open federal grant opportunities specifically filtered by applicant eligibility, with a concrete verb ('Find') and resource ('U.S. federal grant opportunities'). It distinguishes itself from siblings by emphasizing eligibility-based filtering and providing outcome details like deadlines and award amounts.

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?

The description implies when to use the tool (when seeking open grants for a specific organization type) and explains the unique filtering approach. It doesn't explicitly mention alternatives or when not to use it, but the eligibility emphasis makes the use case clear.

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

A4.4/5.0
Disambiguation5/5

Each tool addresses a distinct aspect: checking a specific opportunity, searching eligible opportunities, and examining historical awards. No overlap exists between them.

Naming Consistency4/5

Two tools follow a clear verb_noun pattern (check_grant_eligibility, find_federal_grants), while grant_program_history uses a noun phrase. The style is consistent with snake_case and descriptive names, but the slight deviation prevents a perfect score.

Tool Count5/5

Three tools are well-scoped for the domain, covering search, eligibility verification, and historical context without redundancy. The count fits the server's focused purpose.

Completeness5/5

The tool surface fully supports the stated purpose: find eligible grants, check a specific one, and validate funding expectations. No critical gaps or dead ends exist for this workflow.

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