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Build Analytic Apps for MCP Tools

Analytic apps used through the Alteryx MCP Server should be designed for machine readability. AI uses analytic app metadata, interface parameter names, and output structure to determine what the analytic app does, when to use it, and how to call it.

Design the analytic app like a tool API. Give the AI clear inputs, a clear purpose, and a structured output that contains only the information the AI needs.

For details about how analytic apps are used through MCP, go to Alteryx MCP Server Toolsets. To set up workflow shortcuts for analytic apps, go to Set Up Assets.

Name Interface Tools Clearly

Use clear, descriptive names for Interface Tools. Start from Designer:

  1. Select an Interface tool.

  2. Open the tool Configuration window.

  3. Select the Annotation tab.

  4. Update the Name field.

For analytic apps and macros, many Interface tools appear as Question constants, and the constant name corresponds to the tool Name field on the Annotation tab.

Don't keep default names or generated IDs. Use names that make the expected input obvious without opening the workflow logic.

Good examples:

  • customer_id

  • start_date

  • end_date

  • region

  • include_inactive_accounts

Avoid names such as:

  • Text Box 1

  • Drop Down 2

  • parameter

  • value

Set App Metadata

To help the AI understand when to use the analytic app, give the app a clear name and description.

  1. Open the Workflow Configuration window by selecting an empty area on the canvas.

  2. Select the Meta Info tab.

  3. Enter a name in the Custom field under Workflow Name. Good app names describe the business action or result. Avoid generic names such as Workflow 1, Test App, or Calculator.

  4. Enter a description in the Description field. A useful description should explain what the app does, when to use it, and what inputs it expects. Example description:

    Calculates customer renewal risk for a selected region and date range. Use this app when a user asks which accounts are most likely to churn or which renewal segments need attention.

Return Structured Results

Use 1 of these approaches:

  • Output standard tabular data when a row-and-column structure is sufficient.

  • If the result is more complex, serialize the relevant content, such as JSON, into the CSV so the output is easier for the AI to interpret.

Don't use YXDB files or images for AI-facing outputs. These data types aren't supported. Structured output returned as JSON is limited to 1000 rows by default.

Keep Packages within MCP Limits

Workflow and analytic app packages must stay within MCP registration limits when they are processed for MCP use. Default limits include:

Limit

Default

Workflow package ZIP bundle download size.

750 MB

Standalone or primary workflow XML file size.

200 MB

Decompressed workflow package contents.

1.5 GB

Structured output rows returned as JSON.

1000

Trim Output Fields

Use a Select tool before the final output to return only the fields the AI needs. Remove helper columns, debug fields, duplicate identifiers, and low-value metadata.

Follow MCP Tool Name Requirements

  • Tool names must match this regular expression pattern: ^[a-zA-Z0-9_-]{1,64}$.

  • Use only letters, numbers, underscores, and hyphens.

  • Don't use periods, spaces, or special characters.

  • Use clear names with prefixes: [prefix]_[action]_[optional_qualifier].

Examples:

  • finance_calculate_customer_risk

  • sales_get_pipeline_summary

  • marketing_compare_campaigns

Checklist

  • Set a clear Name for every interface tool.

  • Don't use default Interface tool names or generated IDs.

  • Add a descriptive app name and description in Workflow Configuration > Meta Info.

  • Return structured, AI-facing results.

  • Use supported output types.

  • Keep workflow and analytic app packages within MCP limits.

  • Serialize complex results into a supported CSV output when needed.

  • Remove fields the AI doesn't need.

  • Don't use YXDB or image outputs.

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