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ivossos

FCCS MCP Agentic Server

by ivossos

get_dimensions

Retrieve all dimensions from Oracle EPM Cloud FCCS applications to manage financial consolidation and close processes.

Instructions

Get list of dimensions in the application / Obter lista de dimensoes na aplicacao

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The main tool handler function that executes the get_dimensions logic by calling the FCCS client and formatting the response.
    async def get_dimensions() -> dict[str, Any]:
        """Get list of dimensions in the application / Obter lista de dimensoes na aplicacao.
    
        Returns:
            dict: List of dimensions with their types.
        """
        dimensions = await _client.get_dimensions(_app_name)
        return {"status": "success", "data": dimensions}
  • The tool schema definition including name, description, and input schema (empty object since no parameters required).
    {
        "name": "get_dimensions",
        "description": "Get list of dimensions in the application / Obter lista de dimensoes na aplicacao",
        "inputSchema": {
            "type": "object",
            "properties": {},
        },
    },
  • Registration of the get_dimensions tool handler in the central TOOL_HANDLERS dictionary used by the agent.
    # Dimensions
    "get_dimensions": dimensions.get_dimensions,
    "get_members": dimensions.get_members,
    "get_dimension_hierarchy": dimensions.get_dimension_hierarchy,
  • The underlying FCCS client helper method that implements the API calls or mock data retrieval for dimensions, called by the tool handler.
    async def get_dimensions(self, app_name: str) -> dict[str, Any]:
        """Get dimensions / Obter dimensoes."""
        if self.config.fccs_mock_mode:
            return MOCK_DIMENSIONS
    
        # Try multiple endpoints
        endpoints = [
            f"/{app_name}/dimensions{self._get_query_params()}",
            f"/{app_name}/dimensions",
            f"/{app_name}/metadata/dimensions{self._get_query_params()}",
            f"/{app_name}/metadata/dimensions",
        ]
    
        for endpoint in endpoints:
            try:
                response = await self._client.get(endpoint)
                if response.status_code == 200:
                    return response.json()
            except Exception:
                continue
    
        # Fallback to standard FCCS dimensions
        return {
            "items": [
                {"name": "Years", "type": "Time"},
                {"name": "Period", "type": "Time"},
                {"name": "Scenario", "type": "Scenario"},
                {"name": "View", "type": "View"},
                {"name": "Entity", "type": "Entity"},
                {"name": "Consolidation", "type": "Consolidation"},
                {"name": "Account", "type": "Account"},
                {"name": "ICP", "type": "ICP"},
                {"name": "Data Source", "type": "Data Source"},
                {"name": "Movement", "type": "Movement"},
                {"name": "Multi-GAAP", "type": "Multi-GAAP"},
            ],
            "note": "Standard FCCS dimensions (endpoint not available)"
        }
  • Inclusion of dimensions.TOOL_DEFINITIONS (containing get_dimensions schema) in the aggregated ALL_TOOL_DEFINITIONS list exposed via get_tool_definitions() for MCP.
    ALL_TOOL_DEFINITIONS = (
        application.TOOL_DEFINITIONS +
        jobs.TOOL_DEFINITIONS +
        dimensions.TOOL_DEFINITIONS +
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 only states the action of getting a list, without mentioning whether this is a read-only operation, if it requires authentication, potential rate limits, or the format of the returned data. This leaves significant gaps in understanding the tool's behavior.

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 concise and front-loaded, using a single sentence in two languages to convey the core purpose without unnecessary details. However, the bilingual repetition slightly reduces efficiency, preventing a perfect score for optimal brevity.

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 simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate but lacks depth. It does not explain what 'dimensions' entail in this context or provide any behavioral context, which could be helpful for an AI agent despite the low complexity.

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?

The tool has 0 parameters, and the input schema has 100% description coverage, so there is no need for parameter details in the description. The description appropriately focuses on the tool's purpose without redundant parameter information, earning a high baseline 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 verb 'Get' and resource 'list of dimensions in the application' in both English and Portuguese, making the purpose unambiguous. However, it does not explicitly differentiate from sibling tools like 'get_dimension_hierarchy' or 'get_members', which might also retrieve dimension-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, such as 'get_dimension_hierarchy' or 'get_members', nor does it mention any prerequisites or context for usage. It simply states what the tool does without indicating appropriate scenarios or 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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