Federal Awards to Ticker Mini

Federal award data names the entity that signed, not the company whose revenue line it lands on, so a subsidiary award never joins to a ticker. This Actor maps awards to the listed parent and, crucially, states why: matchBasis names the reason and matchConfidence grades it, and an award it cannot map is kept rather than quietly dropped.

What it does

• States the basis for every match in matchBasis and grades it in matchConfidence, so a mapping is auditable rather than asserted.
• Keeps the unmatched. An award it cannot map to a listed company still comes back, so you can see the coverage instead of assuming it.
• Two modes. Awards returns one record per award, rollup totals by ticker with awardCount and the agencies involved.
• Covers six award types: contracts, grants, IDVs, loans, direct payments and other.
• Carries the awarding agency on every record, which is what turns a total into a story about who is buying.
• Filterable by keyword, so a run can be scoped to one programme rather than the whole feed.

Use cases

You need to	How this Actor does it
Size a company's federal revenue	Use rollup mode and read value against awardCount
Audit a mapping before you trust it	Read matchBasis and matchConfidence on each award
See coverage honestly	Leave Matched only off and count how many awards mapped
Find who a programme pays	Set a keyword and group by tickerSymbol
Track an agency's spend	Group by awardingAgency
Feed a trading agent	Call the Actor over MCP and let the model ask for what it needs

Quick start

1. Click Try for free.
2. Leave Mode on awards for one record per award, or switch it to rollup for totals per ticker.
3. Pick the Award types you want: contracts, grants, IDVs, loans, direct payments or other.
4. Set Awards to read, and turn on Matched only if the unmapped awards are noise for you.
5. Click Start. Rows appear within seconds.
6. Export as JSON, CSV, Excel or XML, or read the dataset over the API.

Input

Field	Type	Default	What it controls
mode	string	awards	awards returns a record per award, rollup totals by ticker
awardTypes	string	contracts	Which award type to read
keyword	string	empty	Scopes the run to awards matching this term
awardsToRead	integer	100	How many awards to read before mapping
matchedOnly	boolean	false	Drops the awards that could not be mapped to a listed company
maxItems	integer	0	Caps how many records are returned

{
    "mode": "awards",
    "awardTypes": "contracts",
    "awardsToRead": 100,
    "matchedOnly": false
}

Output

One dataset item per award in awards mode, one per ticker in rollup mode. An award with no listed parent comes back with the mapping fields empty rather than being dropped, so coverage is visible.

Field group	Fields
Mapping	status, tickerSymbol, listedName, matchBasis, matchConfidence
Award	recipientName, value, awardingAgency, startDate, url
Rollup mode	awardCount, agencies, awardsRead

{
    "status": "ok",
    "tickerSymbol": "LMT",
    "listedName": "Lockheed Martin Corporation",
    "recipientName": "LOCKHEED MARTIN AERONAUTICS COMPANY",
    "matchBasis": "subsidiary name match",
    "matchConfidence": "high",
    "value": 184220500.0,
    "awardingAgency": "Department of Defense",
    "startDate": "2026-07-14",
    "url": "https://www.usaspending.gov/award/CONT_AWD_0184"
}

Integrations

Run it over the API and get the rows back in one call:

curl -X POST "https://api.apify.com/v2/acts/publicmoney~awards-ticker-mini/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"mode": "awards", "awardTypes": "contracts", "awardsToRead": 100, "matchedOnly": false}'

From Python:

from apify_client import ApifyClient

client = ApifyClient("YOUR_TOKEN")
run = client.actor("publicmoney/awards-ticker-mini").call(run_input={"mode": "awards", "awardTypes": "contracts", "awardsToRead": 100, "matchedOnly": false})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["tickerSymbol"], item["value"])

Give an AI agent the Actor over MCP:

{
    "mcpServers": {
        "apify": {
            "url": "https://mcp.apify.com/?actors=publicmoney/awards-ticker-mini"
        }
    }
}

Schedules run it on any cron, webhooks fire when a run finishes, and platform integrations push the dataset to Google Sheets, Slack, Airtable, Zapier or your own endpoint.

Cost

Pay per event, so you pay for records rather than compute time.

Event	Free tier	Top volume tier
Award record	$0.01	$0.004
Actor start	$0.00005 per GB	Same

Two things are charged. The award record above is this Actor's own event. On top of that it runs the USAspending Actor as a child run on your account, which charges its own per-record price and will not appear in this Actor's usage total. Awards to read is the lever. A record that returned no data is never charged.

Troubleshooting

Issue	Solution
Most awards have no ticker	Most federal recipients are not listed companies. That is the real coverage, which is why unmatched awards are kept rather than hidden.
A mapping looks wrong	Read matchBasis. It names the reason, so you can reject the ones whose basis you do not accept, and matchConfidence grades it.
Rollup totals differ from a company's reported revenue	They should. This is federal award value, not booked revenue, and the timing and the entity boundary both differ.
The run costs more than the record price suggests	The USAspending child Actor charges its own per-record price on your account, outside this Actor's usage total.
Fewer records than Awards to read	The cap applies to awards read before mapping, and Matched only then drops the unmapped ones.

FAQ

Why do federal awards not already carry a ticker?

Because the award names the entity that signed the contract, which is usually a subsidiary or a division. Joining that to a listed parent is the work, and it is the reason this Actor exists.

How do I know a mapping is right?

You read matchBasis, which names why the match was made, and matchConfidence, which grades it. Nothing is asserted without a stated reason.

Why keep the awards that did not map?

Because dropping them hides the coverage. An answer that silently covers 30 percent of the feed looks the same as one that covers 90, and you would have no way to tell.

Is this the same as a company's reported revenue?

No. It is federal award value, which differs from booked revenue in timing, in entity boundary and in whether the award is ever fully exercised.

Why is it priced above the single-source Actors?

One record fans out into a child run against the USAspending Actor, which charges its own per-record price on your account.

Do I need a USAspending API key?

No. You need an Apify token to call the Actor over the API. No USAspending credential is involved anywhere.

Can I get this data in Python?

Yes, with the apify-client package as shown above. It returns parsed JSON, so there is no HTML or response handling on your side.

Can I get the data into Excel or Google Sheets?

Yes. Export the dataset as XLSX or CSV, or connect the Google Sheets integration so each run appends to a sheet.

Can an AI agent call this Actor?

Yes. Add it to an MCP client with the config above and the model can request what it needs on its own. Every record is flat JSON with named fields, so no post-processing is needed.

Is it legal to scrape USAspending?

This Actor reads public USAspending data that needs no login and collects no personal data. Scraping public data is generally lawful, and how you store, redistribute or act on market data is governed by your own agreements and local rules. Take your own legal advice for your use case.

Changelog

• 0.0.1 First release. Awards and rollup modes with stated match basis.

Feedback

Found a field USAspending publishes that this Actor misses, or an input it rejects? Open an issue on the Issues tab with the input and what you expected. A daily test runs every Actor in the fleet against live sources, so parser fixes ship fast.