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3a3

Fujitsu Social Digital Twin MCP Server

by 3a3

get_simdata

Retrieve the complete configuration and parameter set for a simulation dataset, including region settings, time ranges, and scenario parameters, using the dataset ID.

Instructions

Retrieves the complete configuration and parameter set for a specific simulation dataset, including region settings, time ranges, and scenario parameters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
simdata_idYes
ctxNo

Implementation Reference

  • The MCP tool handler for 'get_simdata'. Decorated with @mcp.tool(), this async function takes a simdata_id string and optional context, validates the input, creates an API client, calls the underlying API client method, and returns the result or an error.
    @mcp.tool()
    async def get_simdata(simdata_id: str, ctx: Optional[Context] = None) -> Dict[str, Any]:
        """Retrieves the complete configuration and parameter set for a specific simulation dataset, 
        including region settings, time ranges, and scenario parameters."""
        try:
            if not simdata_id:
                return format_api_error(400, "simdataId required")
            
            async with await get_http_client() as client:
                api_client = FujitsuSocialDigitalTwinClient(client)
                result = await api_client.get_simdata(simdata_id)
            return result
        except Exception as e:
            logger.error(f"Simdata retrieval error: {e}")
            return format_api_error(500, str(e))
  • The API client method that actually performs the HTTP GET request to /api/simdata/{simdata_id}. This is the underlying implementation called by the tool handler.
    async def get_simdata(self, simdata_id: str) -> Dict[str, Any]:
        try:
            response = await self.client.get(f"/api/simdata/{simdata_id}")
            response.raise_for_status()
            return format_simulation_result(response.json())
        except httpx.HTTPStatusError as e:
            logger.error(f"Simulation data retrieval error: {e}")
            return format_api_error(e.response.status_code, str(e))
        except Exception as e:
            logger.error(f"Unexpected error retrieving simulation data: {e}")
            return format_api_error(500, str(e))
  • The tool is registered as an MCP tool via the @mcp.tool() decorator on line 513. The decorator registers the function with the FastMCP server instance named 'mcp'.
    @mcp.tool()
    async def get_simdata(simdata_id: str, ctx: Optional[Context] = None) -> Dict[str, Any]:
        """Retrieves the complete configuration and parameter set for a specific simulation dataset, 
        including region settings, time ranges, and scenario parameters."""
        try:
            if not simdata_id:
                return format_api_error(400, "simdataId required")
            
            async with await get_http_client() as client:
                api_client = FujitsuSocialDigitalTwinClient(client)
                result = await api_client.get_simdata(simdata_id)
            return result
        except Exception as e:
            logger.error(f"Simdata retrieval error: {e}")
            return format_api_error(500, str(e))
  • Helper function 'format_simulation_result' used to wrap successful API responses into a standardized format with success=True.
    def format_simulation_result(result: Dict[str, Any]) -> Dict[str, Any]:
        return {
            "success": True,
            "data": result
        }
  • Helper function 'format_api_error' used to wrap error responses into a standardized format with success=False.
    def format_api_error(status_code: int, error_detail: str) -> Dict[str, Any]:
        return {
            "success": False,
            "status_code": status_code,
            "error": error_detail
        }
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It states 'retrieves' indicating a read operation, but does not disclose side effects, error behavior, authentication needs, or what happens if the simdata_id does not exist.

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 a single sentence, concise and to the point. It avoids verbosity, but could be structured to include more details without being wordy.

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?

While the tool is simple (single required parameter), the description lacks information about the output format. There is no output schema, so the description should describe what is returned. It mentions contents but not structure. Adequate but not complete.

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

Parameters1/5

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

Schema description coverage is 0%. The description does not explain the parameters (simdata_id and ctx). It mentions 'region settings, time ranges, scenario parameters' but these are not parameters of the tool.

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 retrieves the complete configuration and parameter set for a simulation dataset. It lists example contents (region settings, time ranges, scenario parameters). However, it does not explicitly distinguish from sibling tools like list_simdata or get_simulation_result.

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 on when to use this tool versus alternatives. There is no mention of when not to use it, prerequisites, or context. The usage is only implied by the description.

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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