This record as markdown: /tools/io-github-dave-london-npm/request.md
What request does on Npm
AI agents invoke request to trigger actions in Npm. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why request is rated High
This tool executes arbitrary HTTP requests via curl to any URL with any method/headers/body. An AI agent could use it to exfiltrate data, trigger webhooks, interact with internal services, or perform SSRF attacks. It runs an external process (curl) whose effects depend entirely on the arguments provided, placing it firmly in the Execute category with high severity due to the broad blast radius.
From the tool's definition Makes an HTTP request via curl and returns structured response data (status, headers, body, timing).
Attacks that exploit this kind of access
The rule that runs request safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Npm, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For request, this is the rule to start with:
request stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Npm, apply this rule, and every request call is checked against it from then on.
Questions about request
Makes an HTTP request via curl and returns structured response data (status, headers, body, timing). It is categorised as a Execute tool in the Npm MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Npm MCP server in PolicyLayer and add a rule for request: 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 Npm. Nothing to install.
request is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the request 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. 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 is provided by the Npm MCP server (Dave-London/Pare). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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