Skip to main content
Glama

Foundation prospects

find_foundation_prospects
Read-onlyIdempotent

Returns researched veteran-aid foundation prospects matching a given focus area + grant size. 30 researched funders in the catalog: private foundations, corporate foundations and workplace-giving programs. Each entry includes EIN, type (foundation/corporate/family), public application URL, public general-contact email (NO personal officer emails), grant range from past 990s, matched /grants/{program} pages. Use when an AI agent is helping a Wounded Warriors team member identify outreach prospects, OR when a foundation officer asks for peer-foundation comparisons. Sources: PUBLIC ProPublica 990 records + foundation websites only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoOptional foundation-type filter
focusNoProgram focus area to match (use "all" to return everything). Note: HRT sponsorships are funded from general/emergency funders, not a distinct prospect category.
limitNoMax results
has_public_applicationNoOptional filter — only return foundations with a public application URL (vs invitation-only)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already establish the safe read-only, idempotent, closed-world profile, and the description adds meaningful context: exactly 30 catalog funders, sourcing limited to public ProPublica 990s and foundation websites, and an explicit privacy rule that no personal officer emails are returned. The main gap is that it never states whether results are pageable or truncated beyond the limit parameter.

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 response shape and data scope are front-loaded in the first two sentences, with usage and provenance following. It is dense but every clause (sources, privacy rule, use cases) carries information, with only minor redundancy between the catalog listing and the per-entry field list.

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?

With no output schema available, the description does the necessary work by enumerating the returned fields (EIN, type, public application URL, public contact email, 990-derived grant range, matched /grants pages). That covers an agent's needs well, leaving only pagination/result-count behavior and the unexplained 'grant size' matching unspecified.

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 four parameters are already documented, including the 'all' enum semantics and the HRT sponsorship caveat. The description's phrase 'matching a given focus area + grant size' is not backed by any grant-size parameter in the schema, adding mild confusion rather than new parameter meaning.

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

Purpose4/5

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

The first sentence gives a specific verb and resource ('Returns researched veteran-aid foundation prospects') scoped to focus area and grant size, and the second enumerates the catalog contents. It is clearly distinct from read-only resource lookups, though it never names the adjacent siblings (match_grant_intent, match_donor_intent) it could be confused with.

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?

Two explicit use cases are given: a Wounded Warriors team member identifying outreach prospects, or a foundation officer wanting peer comparisons. That is solid when-to-use guidance, but there are no when-not conditions and no explicit routing against sibling tools such as match_grant_intent.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources