Skip to main content
Glama
snahrup

Microsoft Fabric MCP Server

by snahrup

refresh_dataset

Refresh Power BI datasets to update data and maintain accuracy for reporting and analysis.

Instructions

Refresh a Power BI dataset

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
datasetIdYesThe ID of the dataset to refresh

Implementation Reference

  • The implementation of the refresh logic that calls the Power BI API.
    async refreshDataset(datasetId: string): Promise<void> {
      try {
        await this.apiClient.post(`/datasets/${datasetId}/refreshes`);
      } catch (error) {
        console.error('Error refreshing dataset:', error);
        throw error;
      }
    }
  • The MCP tool handler for 'refresh_dataset' that invokes the powerBIClient.
    case 'refresh_dataset': {
      const { datasetId } = RefreshDatasetSchema.parse(args);
      await powerBIClient.refreshDataset(datasetId);
      return {
        content: [
          {
            type: 'text',
            text: `Dataset ${datasetId} refresh initiated successfully`,
          },
        ],
      };
    }
  • Zod schema definition for the 'refresh_dataset' tool input.
    const RefreshDatasetSchema = z.object({
      datasetId: z.string().describe('The ID of the dataset to refresh'),
    });
  • src/index.ts:83-95 (registration)
    Registration of the 'refresh_dataset' tool in the MCP server tool list.
      name: 'refresh_dataset',
      description: 'Refresh a Power BI dataset',
      inputSchema: {
        type: 'object',
        properties: {
          datasetId: {
            type: 'string',
            description: 'The ID of the dataset to refresh',
          },
        },
        required: ['datasetId'],
      },
    },
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. 'Refresh' implies a mutation/write operation, but the description doesn't disclose whether this requires specific permissions, whether it's asynchronous/synchronous, what happens to dependent reports, or potential rate limits. For a mutation tool with zero annotation coverage, this is inadequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a simple tool with one parameter and gets straight to the point without unnecessary elaboration.

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 mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'refresh' entails (full/incremental, triggers recalculation), what the response looks like (success/failure indicators), or error conditions. Given the complexity of dataset refresh operations in Power BI, more context is needed.

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 already documents the single 'datasetId' parameter completely. The description adds no additional parameter context beyond what's in the schema (like format examples or where to find dataset IDs). Baseline 3 is appropriate when the schema does all the parameter documentation work.

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 action ('refresh') and resource ('Power BI dataset'), making the tool's purpose immediately understandable. However, it doesn't differentiate this tool from potential sibling tools like 'execute_dax_query' or 'upload_to_datawarehouse' that might also interact with datasets in different ways.

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 prerequisites (like needing an existing dataset), when refresh is appropriate versus other dataset operations, or what happens after refresh. With siblings like 'get_powerbi_datasets' and 'execute_dax_query', this gap is significant.

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/snahrup/microsoft-fabric-mcp'

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