crossref-datacitations.citations.to_dataset
Find scholarly works (journal articles, preprints) that cite a given dataset DOI. Returns each citing work's DOI, work type, publisher member ID, and the citation timestamp. Useful for measuring dataset reuse/impact or tracing which papers relied on a specific dataset. Data: api.crossref.org/beta...
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What crossref-datacitations.citations.to_dataset does on Apibase
AI agents call crossref-datacitations.citations.to_dataset to retrieve information from Apibase 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 |
|---|---|---|---|
rows | integer | — | Number of citation events to return (1-500, default 20) |
dataset_doi | string | Yes | DOI of the dataset to find citing works for (e.g. "10.1037/t00742-000") |
Parameters from the server's own tool schema.
Why crossref-datacitations.citations.to_dataset is rated Low
Retrieves scholarly citation metadata with no side effects, authentication, or data modification capabilities.
From the tool's definition Find scholarly works that cite a dataset. Returns DOI, work type, publisher member ID, timestamp.
Attacks that exploit this kind of access
The rule that runs crossref-datacitations.citations.to_dataset safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Apibase, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For crossref-datacitations.citations.to_dataset, this is the rule to start with:
crossref-datacitations.citations.to_dataset 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 Apibase, apply this rule, and every crossref-datacitations.citations.to_dataset call is checked against it from then on.
Questions about crossref-datacitations.citations.to_dataset
Find scholarly works (journal articles, preprints) that cite a given dataset DOI. Returns each citing work's DOI, work type, publisher member ID, and the citation timestamp. Useful for measuring dataset reuse/impact or tracing which papers relied on a specific dataset. Data: api.crossref.org/beta/datacitations (CrossRef Data Citations API), no auth required, CC0 metadata, ~5-day delay between deposit and API appearance. It is categorised as a Read tool in the Apibase MCP Server, which means it retrieves data without modifying state.
crossref-datacitations.citations.to_dataset accepts 2 parameters: rows, dataset_doi. Required: dataset_doi. The full parameter table on this page comes from the server's own tool schema.
Register the Apibase MCP server in PolicyLayer and add a rule for crossref-datacitations.citations.to_dataset: 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 Apibase. Nothing to install.
crossref-datacitations.citations.to_dataset 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 crossref-datacitations.citations.to_dataset 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 crossref-datacitations.citations.to_dataset. 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.
crossref-datacitations.citations.to_dataset is provided by the Apibase MCP server (apibase-mcp-client). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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