datasets_producthunt_products_facets
Facet the Product Hunt products dataset. Returns distribution counts over the Product Hunt products dataset (dataset id enum value producthunt-products), honoring the same filters as search. Facet enum: topic, launch_year, pricing_type, product_state.
This record as markdown: /tools/crawlora-mcp/datasets-producthunt-products-facets.md
What datasets_producthunt_products_facets does on Crawlora
AI agents call datasets_producthunt_products_facets to retrieve information from Crawlora 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 |
|---|---|---|---|
q | string | — | Full-text query over product name and tagline, max 256 characters |
facet | string | Yes | Facet enum: topic, launch_year, pricing_type, product_state |
maker | string | — | Exact maker-username filter (populated by hydration), max 128 characters |
topic | string | — | Exact topic-slug filter, e.g. artificial-intelligence, max 128 characters |
is_online | boolean | — | true keeps only products still online, false only retired products |
min_votes | integer | — | Minimum upvotes, 0 or greater |
min_rating | number | — | Minimum review rating, from 0 through 5 |
has_website | boolean | — | Website presence filter |
pricing_type | string | — | Exact pricing-type filter, e.g. free, paid, freemium |
launched_after | string | — | Lower bound on first-launch date, an ISO-8601 date (YYYY-MM-DD) |
launched_before | string | — | Upper bound on first-launch date, an ISO-8601 date (YYYY-MM-DD) |
Parameters from the server's own tool schema.
Why datasets_producthunt_products_facets is rated Low
This tool retrieves aggregated statistics and distribution information from a Product Hunt products dataset. Faceting is a read-only operation that counts and groups existing data without creating, modifying, deleting, or executing any operations. The blast radius of misuse is minimal—worst case returns unwanted statistical insights.
From the tool's definition Tool description states it 'Returns distribution counts' and 'Facet' operations which are query/analysis operations with no modification capability.
Risk signalsHigh parameter count (11 properties)
Attacks that exploit this kind of access
The rule that runs datasets_producthunt_products_facets safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Crawlora, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For datasets_producthunt_products_facets, this is the rule to start with:
datasets_producthunt_products_facets 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 Crawlora, apply this rule, and every datasets_producthunt_products_facets call is checked against it from then on.
Questions about datasets_producthunt_products_facets
Facet the Product Hunt products dataset. Returns distribution counts over the Product Hunt products dataset (dataset id enum value producthunt-products), honoring the same filters as search. Facet enum: topic, launch_year, pricing_type, product_state. It is categorised as a Read tool in the Crawlora MCP Server, which means it retrieves data without modifying state.
datasets_producthunt_products_facets accepts 11 parameters: q, facet, maker, topic, is_online, min_votes, min_rating, has_website, pricing_type, launched_after, launched_before. Required: facet. The full parameter table on this page comes from the server's own tool schema.
Register the Crawlora MCP server in PolicyLayer and add a rule for datasets_producthunt_products_facets: 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 Crawlora. Nothing to install.
datasets_producthunt_products_facets 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 datasets_producthunt_products_facets 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 datasets_producthunt_products_facets. 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.
datasets_producthunt_products_facets is provided by the Crawlora MCP server (crawlora-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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