fake_data
Generate realistic, reproducible fake test data from a field schema: up to 1,000 records with 44 field types (names, usernames, emails consistent with the name, phones, companies, job titles, US addresses, countries, coordinates, dates, numbers, prices, UUIDs, IPs, URLs, lorem text, enums with we...
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What fake_data does on ScorpTech x402 API
AI agents call fake_data to retrieve information from ScorpTech x402 API 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 |
|---|---|---|---|
seed | integer | — | Reproducible output (a random seed is chosen and returned when omitted) |
count | integer | — | |
fields | object | Yes | Field name => type name, or {type, ...options} (min / max / decimals / from / to / values / weights / start / step / template / value / nullRate / unique) |
format | string | — |
Parameters from the server's own tool schema.
Why fake_data is rated Low
Even though fake_data 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 fake_data safely
PolicyLayer is an MCP gateway: it sits between your AI agents and ScorpTech x402 API, 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 ScorpTech x402 API, apply this rule, and every fake_data call is checked against it from then on.
Questions about fake_data
Generate realistic, reproducible fake test data from a field schema: up to 1,000 records with 44 field types (names, usernames, emails consistent with the name, phones, companies, job titles, US addresses, countries, coordinates, dates, numbers, prices, UUIDs, IPs, URLs, lorem text, enums with weights, sequences, templates referencing other fields, test card numbers), per-field null rate and uniqueness, as JSON, CSV or NDJSON. Seeded (the seed is returned) so the same request gives the same data. Safe by design: only example.* domains, 555-01xx phone numbers, documentation IP ranges and public card test numbers. Price: $0.003 USDC per successful call (x402, Solana). Same tool over HTTPS: POST https://scorptech.it.com/api/x402/v1/fake-data. It is categorised as a Read tool in the ScorpTech x402 API MCP Server, which means it retrieves data without modifying state.
fake_data accepts 4 parameters: seed, count, fields, format. Required: fields. The full parameter table on this page comes from the server's own tool schema.
Register the ScorpTech x402 API 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 ScorpTech x402 API. 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 ScorpTech x402 API MCP server (https://scorptech.it.com/api/x402/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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