Skip to main content
Glama
ivossos

FCCS MCP Agentic Server

by ivossos

get_report_job_status

Check the status of asynchronous report generation jobs in Oracle EPM Cloud FCCS to monitor progress and retrieve results when ready.

Instructions

Get status of an asynchronously running report job / Obter status de um job de relatorio

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesJob ID from async report generation
report_typeNoReport type (default: FCCS)

Implementation Reference

  • The main async handler function that implements the get_report_job_status tool. It calls the FCCS client to retrieve the job status and wraps the result.
    async def get_report_job_status(
        job_id: str,
        report_type: str = "FCCS"
    ) -> dict[str, Any]:
        """Get status of an asynchronously running report job / Obter status de um job de relatorio.
    
        Args:
            job_id: Job ID from async report generation.
            report_type: Report type - FCCS or SDM (default: FCCS).
    
        Returns:
            dict: Job status details.
        """
        result = await _client.get_report_job_status(job_id, report_type)
        return {"status": "success", "data": result}
  • The input schema definition for the get_report_job_status tool, part of TOOL_DEFINITIONS list.
    {
        "name": "get_report_job_status",
        "description": "Get status of an asynchronously running report job / Obter status de um job de relatorio",
        "inputSchema": {
            "type": "object",
            "properties": {
                "job_id": {
                    "type": "string",
                    "description": "Job ID from async report generation",
                },
                "report_type": {
                    "type": "string",
                    "enum": ["FCCS", "SDM"],
                    "description": "Report type (default: FCCS)",
                },
            },
            "required": ["job_id"],
        },
    },
  • Registration of the tool handler in the central TOOL_HANDLERS dictionary used by the agent to dispatch tool calls.
    "generate_report": reports.generate_report,
    "get_report_job_status": reports.get_report_job_status,
    "generate_report_script": reports.generate_report_script,
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 mentions the tool is for async report jobs, which implies it's a read-only status check, but it doesn't detail behavioral traits like error handling, rate limits, authentication needs, or what the status response includes. This leaves significant gaps for a tool with no annotation coverage.

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 with the primary purpose in English, followed by a Portuguese translation. Both sentences are relevant, but the translation adds minimal value for an AI agent, slightly reducing efficiency. Overall, it's well-structured with zero waste.

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?

Given no annotations and no output schema, the description is incomplete. It doesn't explain what the status response includes (e.g., progress, errors, completion), which is critical for an async job tool. With low behavioral transparency and missing output details, it fails to provide sufficient context for effective use.

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 both parameters (job_id and report_type with enum). The description adds no additional parameter semantics beyond what's in the schema, such as format examples or usage context. Baseline 3 is appropriate when the schema does the heavy lifting.

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 tool's purpose: 'Get status of an asynchronously running report job'. It specifies the verb ('Get status') and resource ('report job'), and the Portuguese translation reinforces this. However, it doesn't explicitly distinguish this from the sibling tool 'get_job_status', which appears to be a more general version, so it misses full sibling differentiation.

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 doesn't mention the sibling 'get_job_status' or other related tools like 'list_jobs', nor does it specify prerequisites such as needing a job ID from an async operation. Usage is implied by the purpose but not explicitly stated.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ivossos/fccs-mcp-ag-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server