datasets_steam_reviews_search
Search the steam-reviews dataset. Searches the stored Steam review corpus (the most-helpful reviews per game; one document per appid × recommendation). Full-text q over the review body, filter by app_id, language, or voted_up (positive/negative). Sort enum: votes_desc (most-helpful first, default...
This record as markdown: /tools/crawlora-mcp/datasets-steam-reviews-search.md
What datasets_steam_reviews_search does on Crawlora
AI agents call datasets_steam_reviews_search 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 the review body, max 256 characters |
page | integer | — | Page number, defaults to 1 |
sort | string | — | Sort enum: votes_desc, weighted_desc, date_desc |
app_id | string | — | Exact Steam app id filter |
language | string | — | Review language filter (e.g. english, schinese) |
voted_up | string | — | Recommendation filter: true (positive) or false (negative) |
page_size | integer | — | Page size, defaults to 20 and maxes at 100; page * page_size must be <= 10000 |
Parameters from the server's own tool schema.
Why datasets_steam_reviews_search is rated Low
Even though datasets_steam_reviews_search 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.
Attacks that exploit this kind of access
The rule that runs datasets_steam_reviews_search 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_steam_reviews_search, this is the rule to start with:
datasets_steam_reviews_search 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_steam_reviews_search call is checked against it from then on.
Questions about datasets_steam_reviews_search
Search the steam-reviews dataset. Searches the stored Steam review corpus (the most-helpful reviews per game; one document per appid × recommendation). Full-text q over the review body, filter by app_id, language, or voted_up (positive/negative). Sort enum: votes_desc (most-helpful first, default), weighted_desc, date_desc. It is categorised as a Read tool in the Crawlora MCP Server, which means it retrieves data without modifying state.
datasets_steam_reviews_search accepts 7 parameters: q, page, sort, app_id, language, voted_up, page_size. 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_steam_reviews_search: 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_steam_reviews_search 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_steam_reviews_search 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_steam_reviews_search. 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_steam_reviews_search 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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