request_purchase
Create a pending request. Does not buy anything or move money.
This record as markdown: /tools/2026-ai-product-engineering/request-purchase.md
What request_purchase does on 2026 Ai Product Engineering
AI agents use request_purchase to create or update resources in 2026 Ai Product Engineering, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your 2026 Ai Product Engineering environment.
Why request_purchase is rated Medium
An AI agent can call request_purchase faster than any human can review: one bad instruction and it creates or modifies resources in 2026 Ai Product Engineering by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
The rule that runs request_purchase safely
PolicyLayer is an MCP gateway: it sits between your AI agents and 2026 Ai Product Engineering, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For request_purchase, this is the rule to start with:
request_purchase stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect 2026 Ai Product Engineering, apply this rule, and every request_purchase call is checked against it from then on.
Questions about request_purchase
Create a pending request. Does not buy anything or move money. It is categorised as a Write tool in the 2026 Ai Product Engineering MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the 2026 Ai Product Engineering MCP server in PolicyLayer and add a rule for request_purchase: 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 2026 Ai Product Engineering. Nothing to install.
request_purchase is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the request_purchase 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 request_purchase. 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.
request_purchase is provided by the 2026 Ai Product Engineering MCP server (Iamshoaibhassan/2026-ai-product-engineering). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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