Low Risk

exa_answer_detailed

exa_answer_detailed

How to control exa_answer_detailed ↓

What exa_answer_detailed does on Gigaxity Deep Research

AI agents call exa_answer_detailed to retrieve information from Gigaxity Deep Research without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Low Risk

Why exa_answer_detailed needs a policy

This tool appears to retrieve and return detailed answers from web sources (likely the Exa search API), which is a Read operation—querying data without side effects. Severity is medium rather than low due to potential for information disclosure or misuse in targeted research scenarios, though the blast radius of a misused search/answer tool is limited compared to write, execute, or destructive operations.

From the tool's definition Tool name 'exa_answer_detailed' and its inclusion in a deep research server alongside 'search', 'research', 'synthesize', and 'scrape_as_markdown' indicates data retrieval functionality.

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

How to control exa_answer_detailed

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

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

exa_answer_detailed is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

  1. Create a free account and register Gigaxity Deep Research — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
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Related tools and policies

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Questions about exa_answer_detailed

What does the exa_answer_detailed tool do? +

exa_answer_detailed. It is categorised as a Read tool in the Gigaxity Deep Research MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on exa_answer_detailed? +

Register the Gigaxity Deep Research MCP server in PolicyLayer and add a rule for exa_answer_detailed: 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 Gigaxity Deep Research. Nothing to install.

What risk level is exa_answer_detailed? +

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

Can I rate-limit exa_answer_detailed? +

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

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

exa_answer_detailed is provided by the Gigaxity Deep Research MCP server (yoloshii/gigaxity-deep-research). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Gigaxity Deep Research tool call.

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

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9 Gigaxity Deep Research tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

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