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Microsoft Fabric MCP Server

by snahrup

get_workspaces

Retrieve all Microsoft Fabric and Power BI workspaces to view available data environments for analysis and management.

Instructions

Get all Fabric/Power BI workspaces

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler for 'get_workspaces' tool in the MCP server, which calls powerBIClient.getWorkspaces().
    case 'get_workspaces': {
      const workspaces = await powerBIClient.getWorkspaces();
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify(workspaces, null, 2),
          },
        ],
      };
    }
  • The actual implementation of fetching workspaces from the Power BI API.
    async getWorkspaces(): Promise<any[]> {
      try {
        const response = await this.apiClient.get('/groups');
        return response.data.value;
      } catch (error) {
        console.error('Error fetching workspaces:', error);
        throw error;
      }
    }
  • src/index.ts:96-103 (registration)
    Tool registration for 'get_workspaces'.
    {
      name: 'get_workspaces',
      description: 'Get all Fabric/Power BI workspaces',
      inputSchema: {
        type: 'object',
        properties: {},
      },
    },
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 states what the tool does but doesn't disclose traits like whether it requires authentication, returns paginated results, includes filtering options, or has rate limits. This leaves significant gaps for a read operation.

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 no wasted words. It front-loads the core action and resource, making it easy to parse quickly. Every word contributes directly to understanding the tool's purpose.

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), the description is minimally adequate but lacks depth. Without annotations or output schema, it doesn't explain what 'Get all' entails (e.g., format, scope, limitations), leaving the agent to infer behavior from the name alone.

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 zero parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description appropriately doesn't add parameter details, earning a baseline score of 4 for matching the schema's simplicity.

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 the resource 'all Fabric/Power BI workspaces', making the purpose unambiguous. It doesn't explicitly differentiate from sibling tools like 'get_powerbi_datasets', but the resource specificity (workspaces vs datasets) provides implicit distinction.

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 implies it retrieves workspace information, it doesn't specify use cases, prerequisites, or contrast with sibling tools like 'create_notebook' or 'refresh_dataset' that might operate on workspaces.

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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