Polytomic MCP Server

activate_bulk_sync

Activate or deactivate bulk data synchronization tasks in Polytomic to control when data pipelines run.

Instructions

Activate or deactivate a bulk sync.

Args: id: The bulk sync ID active: True to activate, False to deactivate

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": {
      "id": "<id>"
    },
    "name": "activate_bulk_sync"
  }
}

Input Schema

Name	Required	Description	Default
`id`	Yes
`active`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Mar 18, 2026

TDQS

B3.2/5.0

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 states the action but does not cover critical aspects like required permissions, whether activation/deactivation is reversible, side effects (e.g., on sync executions), rate limits, or error conditions. This leaves significant gaps for a mutation tool.

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 highly concise and well-structured: a brief purpose statement followed by clear parameter explanations in a simple format. Every sentence adds value without redundancy, making it easy to parse and understand quickly.

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

Completeness3/5

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

Given the tool's complexity (a mutation with 2 parameters), no annotations, and an output schema (which reduces need to describe returns), the description is minimally adequate. It covers basic purpose and parameters but lacks behavioral context and usage guidelines, leaving the agent with incomplete information for safe and effective use.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics by explaining 'id' as 'The bulk sync ID' and 'active' as 'True to activate, False to deactivate', which clarifies beyond the schema's basic types. However, it lacks details like ID format or activation implications, keeping it from a perfect score.

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 ('Activate or deactivate') and the resource ('a bulk sync'), making the purpose immediately understandable. However, it does not explicitly differentiate from sibling tools like 'activate_sync' or 'trigger_bulk_sync', which might handle similar activation functions for different resources or contexts.

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 lacks context about prerequisites (e.g., needing an existing bulk sync ID), exclusions, or comparisons to siblings like 'update_bulk_sync' or 'trigger_bulk_sync', leaving the agent to infer usage scenarios.

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