AI agents call extract_emails to retrieve information from Awesome-MCP-Scaffold without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries/searches text to identify and retrieve email addresses. It performs pattern matching and extraction without modifying, executing code, deleting data, or moving money. The operation is informational only with no state changes or irreversible effects.
From the tool's definition Tool name 'extract_emails' and description 'Extract email addresses from text' indicate data retrieval/parsing with no side effects. Similar to sibling tool 'extract_urls' which is also a Read operation.
Documented attack patterns abuse exactly the kind of access extract_emails gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Awesome-MCP-Scaffold, and nothing reaches the server without passing your rules. This is the rule we recommend for extract_emails:
{
"version": "1",
"default": "deny",
"tools": {
"extract_emails": {}
}
}extract_emails is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Extract email addresses from text. It is categorised as a Read tool in the Awesome-MCP-Scaffold MCP Server, which means it retrieves data without modifying state.
Register the Awesome-MCP-Scaffold MCP server in PolicyLayer and add a rule for extract_emails: 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 Awesome-MCP-Scaffold. Nothing to install.
extract_emails is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the extract_emails 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 extract_emails. 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.
extract_emails is provided by the Awesome-MCP-Scaffold MCP server (ww-ai-lab/awesome-mcp-scaffold). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Awesome-MCP-Scaffold, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
24 Awesome-MCP-Scaffold tools catalogued and risk-classified — across an index of 43,000+ MCP servers.