Look up grantmaking organizations by name, topic, or location.
This tool searches 174K+ grantmaking organizations from IRS data using
organization names plus grant-purpose/topic signals. Use it when you know
the funder's name, want aligned funders for a cause area, or want to browse
by location/size/NTEE code. Multi-word searches are ranked by relevance;
simple browse/name fallback results are ordered by total assets.
IMPORTANT: Use search_open_grants when the user needs active grant programs
or RFPs. search_funders is for finding aligned grantmakers, including ones
that may fund by relationship, LOI, or annual cycle rather than a live call.
Args:
query: Search term for a funder name or cause-area phrase.
Example: "Ford Foundation", "global health", "community foundation"
Topic searches work best with 2+ words.
state: Two-letter US state code to filter by funder HQ location.
Example: "CA", "NY", "TX"
city: City name to filter by (case-insensitive).
Example: "San Francisco", "New York"
ntee_code: NTEE classification code to filter by.
Example: "A20" (Arts Organizations), "B" (Education), "E" (Health)
min_assets: Minimum total assets filter in dollars.
Example: 10000000 (foundations with $10M+ assets)
max_assets: Maximum total assets filter in dollars.
Example: 100000000 (foundations with up to $100M assets)
has_er_grants: Filter to foundations that make expenditure responsibility grants
(grants to non-501(c)(3) entities like PBCs, for-profits, and foreign orgs).
Set to True to find only ER-active funders.
funder_type: Optional canonical funder_type to include. Examples:
"community_foundation", "family_foundation", "corporate_foundation",
"private_operating", "operating_nonprofit", "independent_foundation". Use this to narrow to
a specific kind of grantmaker.
exclude_funder_types: Optional list of canonical funder_type codes to exclude
from results. Useful for hiding operating nonprofits that surface
with large "annual_grants" but are not actually grantmakers — e.g.,
exclude_funder_types=["operating_nonprofit"] hides PATH and similar
operating organizations.
grantee_country_codes: Optional list of FIPS 10-4 country codes
(e.g., "UK" for United Kingdom, "IN" for India, "KE" for Kenya,
"SF" for South Africa) to restrict to funders whose grantees are
located in those countries. Use this when the user is asking
for funders that move money into a specific non-US geography.
Country here is the grantee's HQ country, derived from
foundation_grants. When set, the search is forced through the
hybrid path; the ILIKE-only name-match path cannot filter by
country. Distinct from `state`, which filters by the funder's
own US HQ.
country: Optional HQ country name (or list of names) to restrict to
funders headquartered in those countries (e.g., "Germany",
["United States", "Canada"]). Distinct from
`grantee_country_codes` (where the funder's grants land) and
from `state` (US state of HQ). Use when the user asks for
funders based in a specific country — e.g. "European-headquartered
foundations" → country=["Germany","Spain","United Kingdom",
"Switzerland","Netherlands","France"]. US foundations are
included only when "United States" (or "USA") is in the list,
or when the param is omitted.
limit: Maximum number of results to return.
Default: 20, Maximum: 50
Returns:
Dictionary containing:
- results: List of matching foundations with ein, name, city, state,
total_assets, annual_grants, website_url, has_er_grants, has_pris,
funder_type (when populated), topic_match_count (when query
takes the hybrid topic-search path — see below)
- total_returned: Number of results returned
- query_params: The search parameters used
- note: Helpful context about the results
topic_match_count is the number of distinct grant-purpose strings
under this funder that matched the FTS query. It surfaces only on
topical searches (multi-word queries that route to the hybrid path)
and only for 990-filer rows; ILIKE-only and non-990 rows omit the
field. Rule of thumb:
- topic_match_count == 1 → single tangential grant, often noise
(e.g. a credit-union foundation surfacing for "telemedicine"
because of one passing-mention grant)
- topic_match_count >= 3 → substantive topical coverage
Examples:
search_funders(query="community foundation", state="CA")
search_funders(query="global health", min_assets=100000000)
search_funders(ntee_code="E", min_assets=50000000)
search_funders(state="NY", city="New York", limit=10)
search_funders(has_er_grants=True, state="CA")
search_funders(funder_type="community_foundation", state="CA")
search_funders(query="PATH", exclude_funder_types=["operating_nonprofit"])
search_funders(query="global health", grantee_country_codes=["IN"])
search_funders(query="climate resilience", grantee_country_codes=["KE", "SF"])
search_funders(query="youth education", country="Germany")
search_funders(country=["Germany","Spain","Netherlands"])