call_api

THE RISK

Low Risk

Why call_api needs a policy

The description is completely empty, making it impossible to determine what this tool does with confidence. The name 'call_api' is generic and could span multiple categories. Given the server context (Knowledge Base Retrieval), it might be a Read operation, but the name alone could imply Execute or Write as well. Without further evidence, confidence is very low and 'Other' is assigned pending clarification.

From the tool's definition Tool name is 'call_api' with an empty description. The server context is 'Amazon Bedrock Knowledge Base Retrieval MCP Server'.

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

POLICY

How to control call_api

PolicyLayer is an MCP gateway — it sits between your AI agents and Amazon Bedrock Knowledge Base Retrieval MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for call_api:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "call_api": {
      "limits": [
        {
          "counter": "call_api_rate",
          "window": "minute",
          "max": 60,
          "scope": "grant"
        }
      ]
    }
  }
}

call_api gets a rate cap, and everything else on the server is denied unless you say otherwise.

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

SET A RULE FOR THIS TOOL →

Free to start. No card required.

EXPLORE

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Go deeper

The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Tool risk categories → How PolicyLayer classifies MCP tools by what they can do.
MCP tool → What an MCP tool is and how clients discover and call it.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about call_api

What does the call_api tool do? +

call_api. It is categorised as a Other tool in the Amazon Bedrock Knowledge Base Retrieval MCP Server MCP Server, which means it performs auxiliary operations.

How do I enforce a policy on call_api? +

Register the Amazon Bedrock Knowledge Base Retrieval MCP Server MCP server in PolicyLayer and add a rule for call_api: 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 Amazon Bedrock Knowledge Base Retrieval MCP Server. Nothing to install.

What risk level is call_api? +

call_api is a Other tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit call_api? +

Yes. Add a rate_limit block to the call_api 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 call_api completely? +

Set action: deny in the PolicyLayer policy for call_api. 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 call_api? +

call_api is provided by the Amazon Bedrock Knowledge Base Retrieval MCP Server MCP server (awslabs.bedrock-kb-retrieval-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Amazon Bedrock Knowledge Base Retrieval MCP Server tool call.

Start from Amazon Bedrock Knowledge Base Retrieval MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →