spending_search_awards
Search federal awards (contracts, grants, loans) from USAspending.gov by recipient company, keyword, and/or awarding agency, with optional fiscal year and minimum amount. Returns each award's id, recipient, amount, awarding agency, type, start date, and description, sorted by amount.
This record as markdown: /tools/io-github-blackboxfoundry-livedatalink/spending-search-awards.md
What spending_search_awards does on Livedatalink
AI agents call spending_search_awards to retrieve information from Livedatalink without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
limit | number | — | Max rows (default 10, max 50). |
agency | string | — | Awarding agency name, e.g. 'Department of Defense'. |
keyword | string | — | Free-text keyword across the award. |
category | string | — | Award category: 'contracts' (default), 'grants', 'loans', or 'other'. |
recipient | string | — | Recipient company/org name, e.g. 'Lockheed Martin'. |
min_amount | number | — | Minimum award amount in USD. |
fiscal_year | number | — | Federal fiscal year, e.g. 2024. |
Parameters from the server's own tool schema.
Why spending_search_awards is rated Low
This tool retrieves and queries publicly available federal award information from a government database. It has no side effects—it does not create, modify, delete, or execute operations. The search and return of structured data is a classic Read operation.
From the tool's definition Tool description states 'Search federal awards...Returns each award's id, recipient, amount, awarding agency, type, start date, and description'. The verb 'Search' and 'Returns' indicate data retrieval with no modification or execution capability.
Attacks that exploit this kind of access
The rule that runs spending_search_awards safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Livedatalink, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For spending_search_awards, this is the rule to start with:
spending_search_awards is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Livedatalink, apply this rule, and every spending_search_awards call is checked against it from then on.
Questions about spending_search_awards
Search federal awards (contracts, grants, loans) from USAspending.gov by recipient company, keyword, and/or awarding agency, with optional fiscal year and minimum amount. Returns each award's id, recipient, amount, awarding agency, type, start date, and description, sorted by amount. It is categorised as a Read tool in the Livedatalink MCP Server, which means it retrieves data without modifying state.
spending_search_awards accepts 7 parameters: limit, agency, keyword, category, recipient, min_amount, fiscal_year. The full parameter table on this page comes from the server's own tool schema.
Register the Livedatalink MCP server in PolicyLayer and add a rule for spending_search_awards: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Livedatalink. Nothing to install.
spending_search_awards is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the spending_search_awards rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for spending_search_awards. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
spending_search_awards is provided by the Livedatalink MCP server (https://livedatalink.ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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