fake_data
Generate fake test data — users, emails, addresses, credit cards.
This record as markdown: /tools/io-github-kivanccakmak-yaver/fake-data.md
What fake_data does on Yaver
AI agents call fake_data to retrieve information from Yaver 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 |
|---|---|---|---|
type | string | — | user, email, address, uuid, credit_card (default: user) |
count | integer | — | Number of records (max: 20) |
Parameters from the server's own tool schema.
Why fake_data is rated Low
This tool generates synthetic/fake data for testing purposes. It does not read real data, write to any store, or execute commands — it produces fabricated values. Categorized as Read (data generation/retrieval with no side effects). Severity is medium because it generates fake credit card numbers, which could potentially be misused in social engineering or fraud scenarios, even though the data is not real.
From the tool's definition Generate fake test data — users, emails, addresses, credit cards
Attacks that exploit this kind of access
The rule that runs fake_data safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Yaver, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For fake_data, this is the rule to start with:
fake_data 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 Yaver, apply this rule, and every fake_data call is checked against it from then on.
Questions about fake_data
Generate fake test data — users, emails, addresses, credit cards. It is categorised as a Read tool in the Yaver MCP Server, which means it retrieves data without modifying state.
fake_data accepts 2 parameters: type, count. The full parameter table on this page comes from the server's own tool schema.
Register the Yaver MCP server in PolicyLayer and add a rule for fake_data: 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 Yaver. Nothing to install.
fake_data 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 fake_data 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 fake_data. 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.
fake_data is provided by the Yaver MCP server (yaver-cli). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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