Low Risk

get_dataset

Pull rows from a CMS dataset by datasetId (UUID from search_datasets). Returns an array of row objects whose keys are the dataset columns. Supports paging (size/offset), full-text keyword search across the dataset, and exact-match column filters via filters: {COLUMN: VALUE} (column names match th...

Part of the Cms server.

get_dataset is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call get_dataset to retrieve information from Cms without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though get_dataset only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "get_dataset": {}
  }
}

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Get this rule live on your own Cms server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access get_dataset gives an agent. Each links to the full case and the policy that stops it:

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so get_dataset only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the get_dataset tool do? +

Pull rows from a CMS dataset by datasetId (UUID from search_datasets). Returns an array of row objects whose keys are the dataset columns. Supports paging (size/offset), full-text keyword search across the dataset, and exact-match column filters via filters: {COLUMN: VALUE} (column names match the keys in returned rows, e.g. {"State": "TX"}).. It is categorised as a Read tool in the Cms MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_dataset? +

Register the Cms MCP server in PolicyLayer and add a rule for get_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 Cms. Nothing to install.

What risk level is get_dataset? +

get_dataset is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit get_dataset? +

Yes. Add a rate_limit block to the get_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.

How do I block get_dataset completely? +

Set action: deny in the PolicyLayer policy for get_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.

What MCP server provides get_dataset? +

get_dataset is provided by the Cms MCP server (https://gateway.pipeworx.io/cms/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Cms tool call.

Deterministic rules across all 23 Cms tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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