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Jedox MCP Server

by emilabd247

Create Jedox Cube Rule

jedox_create_rule

Create a calculation rule for a Jedox cube with formulas like ['Profit'] = ['Revenue'] - ['Cost']. Supports multi-dimensional qualifiers and immediate activation.

Instructions

Add a calculation rule to a Jedox cube.

Jedox rules use a special syntax with single-quoted element names: ['TargetElement'] = ['ElementA'] + ['ElementB'] ['Profit'] = ['Revenue'] - ['Cost'] ['Growth%'] = (['This Year'] / ['Last Year'] - 1) * 100

Multi-dimensional rules restrict which cells they apply to using dimension qualifiers: ['Profit']:['Jan'] = ['Revenue']:['Jan'] - ['Cost']:['Jan']

Rules take precedence over consolidation. Be careful not to create circular references.

Args:

  • database_id: Numeric ID of the database

  • cube_id: Numeric ID of the cube

  • definition: The rule formula (use single quotes around element names)

  • comment: Optional description (default: empty)

  • activate: Whether to activate the rule immediately (default: true)

Returns: { id, definition, active }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
database_idYes
cube_idYes
definitionYesJedox rule formula. Use single quotes around element names, e.g.: ["Profit"] = ["Revenue"] - ["Cost"]. Note: in JSON you must escape the quotes as \"Profit\" etc.
commentNoOptional comment/description for the rule.
activateNoWhether to activate the rule immediately. Default: true.
Behavior4/5

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

Annotations are sparse (readOnlyHint=false, destructiveHint=false), but the description adds valuable behavioral context: rules take precedence over consolidation, need for single quotes, avoidance of circular references. This goes beyond what annotations provide, earning a 4.

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 front-loaded with a clear purpose, followed by examples and an args list. While slightly lengthy, each section adds necessary information without redundancy. Structured well for an AI agent.

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?

With no output schema, the description explicitly mentions the return format. It covers purpose, syntax, arguments, and behavioral notes. Lacks only explicit alternative tool guidance, but overall complete for a rule creation tool.

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 covers all parameters with descriptions (60% coverage), but the description adds syntax examples and JSON escaping guidance for the 'definition' parameter. This adds modest value beyond schema, justifying a 3.

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 starts with a clear verb and resource: 'Add a calculation rule to a Jedox cube.' This distinguishes it from sibling tools like create_cube or delete_rule, and the specific focus on rules is evident.

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 provides examples and warns about circular references and rule precedence, but it does not explicitly state when to use this tool versus alternatives like set_cell_value or bulk operations. The usage context is implied through syntax examples but lacks exclusions.

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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