api_request

THE RISK

High Risk

Why api_request needs a policy

This tool proxies arbitrary HTTP requests to upstream APIs. The effect depends entirely on the HTTP method and target: GET calls are reads, but POST/PUT/PATCH/DELETE calls can write, modify, or destroy remote data.

From the tool's definition 'Proxy an HTTP request through the gateway to an upstream API target' — triggers external HTTP operations whose effects depend on arguments (method, endpoint, body)

Documented attack patterns abuse exactly the kind of access api_request gives an agent:

POLICY

How to control api_request

PolicyLayer is an MCP gateway — it sits between your AI agents and Shellgate, and nothing reaches the server without passing your rules. This is the rule we recommend for api_request:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "api_request": {
      "limits": [
        {
          "counter": "api_request_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

api_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.

Create a free account and register Shellgate — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

RATE-LIMIT THIS TOOL →

Free to start. No card required.

EXPLORE

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Go deeper

High-risk tools in Shellgate → Every high-risk tool this server exposes, in one view.
All high-risk MCP tools → Every high-risk tool across the catalogue, and the policy pattern that contains them.
The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Agent sandbox → Bounding what an agent can execute and where the boundary should sit.
Least privilege for MCP → Granting agents the minimum tool surface the task needs.
Rate Limiting MCP Tool Calls: A Practical Guide →
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FAQ

Questions about api_request

What does the api_request tool do? +

Proxy an HTTP request through the gateway to an upstream API target. If the response has status. It is categorised as a Execute tool in the Shellgate MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on api_request? +

Register the Shellgate MCP server in PolicyLayer and add a rule for api_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 Shellgate. Nothing to install.

What risk level is api_request? +

api_request is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit api_request? +

Yes. Add a rate_limit block to the api_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.

How do I block api_request completely? +

Set action: deny in the PolicyLayer policy for api_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.

What MCP server provides api_request? +

api_request is provided by the Shellgate MCP server (matthiastjong/shellgate). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Shellgate tool call.

Start from Shellgate, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →