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mParticle MCP Server

mParticle MCP Server

by nmattox
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_all_data_plans

Retrieve all data plans for an mParticle workspace to review event structure and validation rules. Use this to govern data workflows and ensure schemas stay current.

Instructions

Get all data plans for a workspace.

This tool retrieves all data plans from mParticle's Data Planning API.
Data plans define the expected structure and validation rules for your events.

Args:
    workspace_id: The mParticle workspace ID (required)
    
Returns:
    JSON string containing all data plans and their metadata
    
Raises:
    Exception: If API credentials are missing or API request fails

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": {
      "workspace_id": "<workspace_id>"
    },
    "name": "get_all_data_plans"
  }
}

Input Schema

NameRequiredDescriptionDefault
workspace_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

No annotations are present, so the description carries the full behavioral burden. It makes clear this is a retrieval operation, states the return format as a JSON string of data plans and metadata, and discloses that an exception is raised if credentials are missing or the request fails.

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 purpose is front-loaded and the Args/Returns/Raises structure is easy to scan. The second sentence is largely redundant with the first, and the data-plan background sentence is optional, so it is not maximally tight.

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 simple one-parameter read-only tool with an output schema, the description is nearly complete: it explains the argument, the return shape, and failure behavior. The main gap is not guiding the agent toward sibling tools for single-plan or status lookups.

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?

The schema has no property descriptions, and the description only adds 'The mParticle workspace ID (required)' for workspace_id. This identifies the parameter's role but does not provide a format, example, or guidance on how to locate the ID.

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 action and resource: 'Get all data plans for a workspace' and 'retrieves all data plans from mParticle's Data Planning API.' The plural 'all' differentiates it from get_data_plan_by_id, though it does not explicitly name that sibling.

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 intended use case is implied: use this when you need the full set of data plans for a workspace. However, there is no explicit guidance about alternatives like get_data_plan_by_id for a single plan or get_api_status for API health.

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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