AEO Copilot MCP Server

get_index_results

Retrieve raw per-prompt results for an industry index across all 4 LLMs, capturing every cited entity without brand-mention fields.

Instructions

Get raw per-prompt results for an industry index across all 4 LLMs. Same shape as get_results minus the brand-mention fields — every cited entity is captured.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "indexId": "<indexId>"
    },
    "name": "get_index_results"
  }
}

Input Schema

Name	Required	Description	Default
`indexId`	Yes	The index UUID from list_indexes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.2.0Aug 30, 2026

TDQS

A3.8/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the burden of behavioral disclosure. It does convey that the operation is a read ('Get'), covers all 4 LLMs, and captures every cited entity, but it does not disclose details like pagination, exact return fields, error conditions, or any side effects. This is adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two dense sentences with no filler. The main purpose is front-loaded, and the comparison to get_results earns its place by clarifying the output shape.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter tool with no output schema, the description gives enough context for correct invocation: it names the input source, describes the output scope, and references a sibling tool for shape comparison. It could be slightly stronger with explicit usage conditions or exact excluded fields, but it is otherwise complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with indexId documented as 'The index UUID from list_indexes.' The tool description adds no parameter-specific meaning beyond that, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource: 'Get raw per-prompt results for an industry index across all 4 LLMs.' It also distinguishes itself from the sibling get_results by explicitly noting the difference ('minus the brand-mention fields'), so an agent can identify what this tool provides.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description references get_results and explains the key difference, but does not explicitly state when to prefer this tool over get_results or any other sibling. The guidance is implied rather than direct, so an agent must infer the appropriate selection criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.