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AudienseCo

Audiense Insights MCP Server

Official
by AudienseCo

get-audience-insights

Retrieve aggregated audience insights including demographics, behavior, psychographics, and socioeconomic data for marketing analysis.

Instructions

Retrieves aggregated insights for a given audience ID, providing statistical distributions across various attributes. Available insights include demographics (e.g., gender, age, country), behavioral traits (e.g., active hours, platform usage), psychographics (e.g., personality traits, interests), and socioeconomic factors (e.g., income, education status).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audience_insights_idYesThe ID of the audience insights.
insightsNoOptional list of insight names to filter.

Implementation Reference

  • src/index.ts:98-138 (registration)
    Registration of the MCP 'get-audience-insights' tool, including multi-line description, Zod input schema (audience_insights_id and optional insights), and handler that fetches data and formats it as structured text response
    server.tool(
        "get-audience-insights",
        `Retrieves aggregated insights for a given audience ID, providing statistical distributions across various attributes.
        Available insights include demographics (e.g., gender, age, country), behavioral traits (e.g., active hours, platform usage), psychographics (e.g., personality traits, interests), and socioeconomic factors (e.g., income, education status).`,
        {
            audience_insights_id: z.string().describe("The ID of the audience insights."),
            insights: z.array(z.string()).optional().describe("Optional list of insight names to filter."),
        },
        async ({ audience_insights_id, insights }) => {
            const data = await getAudienceInsights(audience_insights_id, insights);
    
            if (!data || !data.insights.length) {
                return {
                    content: [
                        {
                            type: "text",
                            text: `No insights found for audience ${audience_insights_id}.`,
                        },
                    ],
                };
            }
    
            const insightsText = data.insights
                .map(
                    (insight) =>
                        `**${insight.name}**:\n${insight.values
                            .map((val) => `- ${val.key}: ${val.value}%`)
                            .join("\n")}`
                )
                .join("\n\n");
    
            return {
                content: [
                    {
                        type: "text",
                        text: `Audience Insights for ${audience_insights_id}:\n\n${insightsText}`,
                    },
                ],
            };
        }
    );
  • Core handler logic for fetching audience insights from the Audiense API. Constructs query params if insights filter provided and calls the generic makeAudienseRequest to the /audience_insights/{id} endpoint with authentication.
    export async function getAudienceInsights(
        audience_insights_id: string,
        insights?: string[]
    ): Promise<{ insights: { name: string; values: { key: string; value: string }[] }[] } | null> {
        const queryParams = insights ? `?insights=${insights.join(",")}` : "";
        return makeAudienseRequest<{ insights: { name: string; values: { key: string; value: string }[] }[] }>(
            `/audience_insights/${audience_insights_id}${queryParams}`
        );
    }
  • Zod schema for tool inputs: required string audience_insights_id and optional array of strings for insights to filter.
    {
        audience_insights_id: z.string().describe("The ID of the audience insights."),
        insights: z.array(z.string()).optional().describe("Optional list of insight names to filter."),
    },
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes what insights are retrieved but lacks critical behavioral details such as whether this is a read-only operation, potential rate limits, authentication requirements, or the format of the aggregated data. For a tool with no annotations, this is a significant gap in transparency.

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

Conciseness4/5

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

The description is appropriately sized and front-loaded, starting with the core action ('Retrieves aggregated insights') and then listing insight categories. Both sentences earn their place by clarifying scope, but it could be slightly more concise by integrating the list more tightly or omitting minor redundancies.

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

Completeness2/5

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

Given the tool's complexity (retrieving aggregated insights with multiple categories), no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits, response format, error handling, or how insights are aggregated. For a tool with rich potential outputs and no structured support, more context is needed to be fully helpful.

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%, so the schema already documents both parameters ('audience_insights_id' and 'insights'). The description adds value by explaining the types of insights available (e.g., demographics, behavioral traits), which helps contextualize the 'insights' parameter, but it doesn't provide additional syntax or format details beyond what the schema offers. This meets the baseline for high schema coverage.

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

Purpose4/5

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

The description clearly states the tool's purpose with a specific verb ('Retrieves') and resource ('aggregated insights for a given audience ID'), and it distinguishes the type of insights provided (demographics, behavioral traits, psychographics, socioeconomic factors). However, it doesn't explicitly differentiate from sibling tools like 'get-audience-content' or 'get-reports', which might also retrieve audience-related data, so it falls short of a perfect score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get-audience-content' or 'get-reports', nor does it specify prerequisites, exclusions, or contextual cues for selection. Usage is implied through the description of insights but not explicitly stated.

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

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