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
Even though datasets_producthunt_products_facets only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
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.
More on Crawlora, and thousands of servers like it.
This server
Across the catalogue