Low Risk

local_intel_ask

Composite NL query layer. Ask any plain-English question about a ZIP — demographics, market opportunity, restaurant gaps, retail saturation, construction activity, investment signals, healthcare, corridor analysis, recent changes, nearby businesses. Routes internally to the right tools and return...

Part of the Local Intel server.

local_intel_ask is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call local_intel_ask to retrieve information from Local Intel without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though local_intel_ask only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "local_intel_ask": {}
  }
}

See the full Local Intel policy for all 27 tools.

Get this rule live on your own Local Intel server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access local_intel_ask gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so local_intel_ask only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the local_intel_ask tool do? +

Composite NL query layer. Ask any plain-English question about a ZIP — demographics, market opportunity, restaurant gaps, retail saturation, construction activity, investment signals, healthcare, corridor analysis, recent changes, nearby businesses. Routes internally to the right tools and returns a synthesized, sourced answer with confidence score. Best single entry point for humans and LLMs.. It is categorised as a Read tool in the Local Intel MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on local_intel_ask? +

Register the Local Intel MCP server in PolicyLayer and add a rule for local_intel_ask: 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 Local Intel. Nothing to install.

What risk level is local_intel_ask? +

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

Can I rate-limit local_intel_ask? +

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

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

local_intel_ask is provided by the Local Intel MCP server (https://gsb-swarm-production.up.railway.app/api/local-intel/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Local Intel tool call.

Deterministic rules across all 27 Local Intel tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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