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FCCS MCP Agentic Server

by ivossos

generate_report

Generate FCCS reports for Task Manager, Supplemental Data, or Enterprise Journal to support financial consolidation and close processes in Oracle EPM Cloud.

Instructions

Generate FCCS report (Task Manager, Supplemental Data, Enterprise Journal) / Gerar relatorio FCCS

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
group_nameYesGroup name the report is associated with (e.g., 'Task Manager')
report_nameYesName of the report to generate
generated_report_file_nameNoUser-specified name for the generated report
parametersNoReport-specific parameters (Schedule, Period, etc.)
formatNoReport format (default: PDF)
moduleNoModule: FCM (Task Manager) or SDM (Supplemental Data Manager)
emailsNoComma-separated email addresses to receive the report
run_asyncNoRun asynchronously (recommended for larger reports)

Implementation Reference

  • The primary handler function for the 'generate_report' MCP tool. It processes input parameters, constructs the API payload, and delegates to the FCCS client for report generation.
    async def generate_report(
        group_name: str,
        report_name: str,
        generated_report_file_name: Optional[str] = None,
        parameters: Optional[dict[str, Any]] = None,
        format: str = "PDF",
        module: str = "FCM",
        emails: Optional[str] = None,
        run_async: bool = False
    ) -> dict[str, Any]:
        """Generate FCCS report (Task Manager, Supplemental Data, Enterprise Journal) / Gerar relatorio FCCS.
    
        Args:
            group_name: Group name the report is associated with (e.g., 'Task Manager').
            report_name: Name of the report to generate.
            generated_report_file_name: User-specified name for the generated report.
            parameters: Report-specific parameters (Schedule, Period, etc.).
            format: Report format - HTML, PDF, XLSX, CSV (default: PDF).
            module: Module - FCM (Task Manager) or SDM (Supplemental Data Manager).
            emails: Comma-separated email addresses to receive the report.
            run_async: Run asynchronously (recommended for larger reports).
    
        Returns:
            dict: Report generation result or job ID if async.
        """
        report_params = {
            "groupName": group_name,
            "reportName": report_name,
            "format": format,
            "module": module,
            "runAsync": run_async,
        }
        if generated_report_file_name:
            report_params["generatedReportFileName"] = generated_report_file_name
        if parameters:
            report_params["parameters"] = parameters
        if emails:
            report_params["emails"] = emails
    
        result = await _client.generate_report(report_params)
        return {"status": "success", "data": result}
  • JSON schema defining the input parameters, types, descriptions, enums, and required fields for the generate_report tool.
        "name": "generate_report",
        "description": "Generate FCCS report (Task Manager, Supplemental Data, Enterprise Journal) / Gerar relatorio FCCS",
        "inputSchema": {
            "type": "object",
            "properties": {
                "group_name": {
                    "type": "string",
                    "description": "Group name the report is associated with (e.g., 'Task Manager')",
                },
                "report_name": {
                    "type": "string",
                    "description": "Name of the report to generate",
                },
                "generated_report_file_name": {
                    "type": "string",
                    "description": "User-specified name for the generated report",
                },
                "parameters": {
                    "type": "object",
                    "description": "Report-specific parameters (Schedule, Period, etc.)",
                },
                "format": {
                    "type": "string",
                    "enum": ["HTML", "PDF", "XLSX", "CSV"],
                    "description": "Report format (default: PDF)",
                },
                "module": {
                    "type": "string",
                    "enum": ["FCM", "SDM"],
                    "description": "Module: FCM (Task Manager) or SDM (Supplemental Data Manager)",
                },
                "emails": {
                    "type": "string",
                    "description": "Comma-separated email addresses to receive the report",
                },
                "run_async": {
                    "type": "boolean",
                    "description": "Run asynchronously (recommended for larger reports)",
                },
            },
            "required": ["group_name", "report_name"],
        },
    },
  • Maps the 'generate_report' tool name to its handler function (reports.generate_report) in the central TOOL_HANDLERS registry used by the agent.
    # Reports
    "generate_report": reports.generate_report,
    "get_report_job_status": reports.get_report_job_status,
    "generate_report_script": reports.generate_report_script,
  • Aggregates tool definitions from all modules, including reports.TOOL_DEFINITIONS containing the generate_report schema, for exposure via get_tool_definitions().
    ALL_TOOL_DEFINITIONS = (
        application.TOOL_DEFINITIONS +
        jobs.TOOL_DEFINITIONS +
        dimensions.TOOL_DEFINITIONS +
        journals.TOOL_DEFINITIONS +
        data.TOOL_DEFINITIONS +
        reports.TOOL_DEFINITIONS +
        consolidation.TOOL_DEFINITIONS +
        memo.TOOL_DEFINITIONS +
        feedback.TOOL_DEFINITIONS +
        local_data.TOOL_DEFINITIONS
    )
  • Helper function to initialize the global FCCS client instance used by the generate_report handler.
    def set_client(client: FccsClient):
        global _client
        _client = client
    
    
    async def generate_report(
        group_name: str,
        report_name: str,
        generated_report_file_name: Optional[str] = None,
        parameters: Optional[dict[str, Any]] = None,
        format: str = "PDF",
        module: str = "FCM",
        emails: Optional[str] = None,
        run_async: bool = False
    ) -> dict[str, Any]:
        """Generate FCCS report (Task Manager, Supplemental Data, Enterprise Journal) / Gerar relatorio FCCS.
    
        Args:
            group_name: Group name the report is associated with (e.g., 'Task Manager').
            report_name: Name of the report to generate.
            generated_report_file_name: User-specified name for the generated report.
            parameters: Report-specific parameters (Schedule, Period, etc.).
            format: Report format - HTML, PDF, XLSX, CSV (default: PDF).
            module: Module - FCM (Task Manager) or SDM (Supplemental Data Manager).
            emails: Comma-separated email addresses to receive the report.
            run_async: Run asynchronously (recommended for larger reports).
    
        Returns:
            dict: Report generation result or job ID if async.
        """
        report_params = {
            "groupName": group_name,
            "reportName": report_name,
            "format": format,
            "module": module,
            "runAsync": run_async,
        }
        if generated_report_file_name:
            report_params["generatedReportFileName"] = generated_report_file_name
        if parameters:
            report_params["parameters"] = parameters
        if emails:
            report_params["emails"] = emails
    
        result = await _client.generate_report(report_params)
        return {"status": "success", "data": result}
  • Low-level FCCSClient method invoked by the tool handler to make the REST API call for report generation.
    async def generate_report(
        self,
        parameters: dict[str, Any]
    ) -> dict[str, Any]:
        """Generate report / Gerar relatorio."""
        if self.config.fccs_mock_mode:
            return {
                "type": parameters.get("module", "FCM"),
                "status": -1 if parameters.get("runAsync") else 0,
                "details": "In Process" if parameters.get("runAsync") else f"{parameters.get('reportName')}.pdf",
                "links": []
            }
    
        payload = {
            "groupName": parameters.get("groupName"),
            "reportName": parameters.get("reportName"),
            "format": parameters.get("format", "PDF"),
            "module": parameters.get("module", "FCM"),
            "runAsync": parameters.get("runAsync", False),
        }
        if parameters.get("generatedReportFileName"):
            payload["generatedReportFileName"] = parameters["generatedReportFileName"]
        if parameters.get("parameters"):
            payload["parameters"] = parameters["parameters"]
        if parameters.get("emails"):
            payload["emails"] = parameters["emails"]
    
        response = await self._fcm_client.post("/report", json=payload)
        response.raise_for_status()
        return response.json()
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions report generation but doesn't disclose whether this is a read-only or write operation, potential side effects (e.g., file creation, email notifications), performance considerations, or authentication needs. The async parameter hints at performance but isn't explained in the description itself.

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 brief and front-loaded with the primary function. The bilingual repetition ('/ Gerar relatorio FCCS') is slightly redundant but not excessive. It avoids unnecessary elaboration, though it could be more structured by separating the core function from examples.

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

Completeness2/5

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

For a complex tool with 8 parameters, nested objects, no output schema, and no annotations, the description is inadequate. It doesn't explain what the tool returns (e.g., a file, job ID, or status), error conditions, or how parameters interact. The agent lacks context to use this tool effectively beyond basic parameter passing.

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 description coverage is 100%, so the schema fully documents all 8 parameters. The description adds no additional parameter semantics beyond implying FCCS context. It doesn't clarify relationships between parameters (e.g., how 'module' relates to 'group_name') or provide examples beyond the enumerated lists already in the schema.

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 ('Generate') and resource ('FCCS report'), with specific examples of report types (Task Manager, Supplemental Data, Enterprise Journal). It distinguishes itself from other report-generation siblings like 'generate_consolidation_process_report' or 'generate_intercompany_matching_report' by specifying FCCS reports. However, it doesn't explicitly differentiate from 'generate_report_script' which might be related.

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?

No guidance is provided on when to use this tool versus alternatives. While the description mentions specific report types, it doesn't indicate prerequisites, when to choose this over other report tools, or any constraints. The agent must infer usage from parameter names and sibling tool names alone.

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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