fetch_url_and_store · MCP Associative Memory Server MCP

WHAT IT DOES

What fetch_url_and_store does on MCP Associative Memory Server

AI agents use fetch_url_and_store to create or update resources in MCP Associative Memory Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your MCP Associative Memory Server environment.

WHY IT NEEDS A POLICY

Why fetch_url_and_store needs a policy

This tool performs two actions: fetching content from a URL (Read) and storing it in memory (Write). Since Write is more severe than Read, the tool is classified as Write. Misuse could lead to storing malicious or unwanted content into the memory system, or be used to exfiltrate data by fetching attacker-controlled URLs. The blast radius is medium since it affects stored memory but is reversible.

From the tool's definition 'Fetch URL content and store in associative memory' — the tool retrieves external content and writes it into the memory store

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

fetch_url_and_store Rate-limited

fetch_url_and_store 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "fetch_url_and_store": {
      "limits": [
        {
          "counter": "fetch_url_and_store_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches MCP Associative Memory Server, so you can run agents against it safely.

FAQ

Questions about fetch_url_and_store

What does the fetch_url_and_store tool do? +

Fetch URL content and store in associative memory. It is categorised as a Write tool in the MCP Associative Memory Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on fetch_url_and_store? +

Register the MCP Associative Memory Server MCP server in PolicyLayer and add a rule for fetch_url_and_store: 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 MCP Associative Memory Server. Nothing to install.

What risk level is fetch_url_and_store? +

fetch_url_and_store is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit fetch_url_and_store? +

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

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

fetch_url_and_store is provided by the MCP Associative Memory Server MCP server (mako10k/mcp-assoc-memory). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.