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BlazeMeter MCP Server

by pbandreddy

get_test_run_errors_data

Retrieve error report data for a specific test run to analyze performance issues and identify failures in BlazeMeter tests.

Instructions

Get the errors report data for a specified test run (master).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
masterIdYesThe ID of the test run (master) to retrieve the errors report data for.

Implementation Reference

  • The main handler function that fetches the errors report data from the BlazeMeter API for a given test run masterId. It constructs the API URL, authenticates with basic auth from environment variables, performs a GET request, handles errors, and returns the JSON data or an error object.
    const executeFunction = async ({ masterId }) => {
      const baseUrl = process.env.BASE_URL; // loaded from .env
      const username = process.env.BZM_USERNAME; // loaded from .env
      const password = process.env.BZM_PASSWORD; // loaded from .env
    
      try {
        // Construct the URL for the errors report data
        const url = new URL(`${baseUrl}/api/v4/masters/${masterId}/reports/errorsreport/data`);
    
        // Set up headers for the request
        const headers = {
          'Authorization': 'Basic ' + Buffer.from(`${username}:${password}`).toString('base64'),
          'Accept': 'application/json'
        };
    
        // Perform the fetch request
        const response = await fetch(url.toString(), {
          method: 'GET',
          headers
        });
    
        // Check if the response was successful
        if (!response.ok) {
          let errorData;
          try {
            errorData = await response.json();
          } catch (jsonErr) {
            errorData = await response.text();
          }
          throw new Error(`HTTP ${response.status} ${response.statusText}: ${typeof errorData === 'string' ? errorData : JSON.stringify(errorData)}`);
        }
    
        // Parse and return the response data
        const data = await response.json();
        return data;
      } catch (error) {
        if (error instanceof Error) {
          return { error: error.message };
        } else {
          return { error: 'Unknown error occurred while getting errors report data.' };
        }
      }
    };
  • The tool schema definition including the name 'get_test_run_errors_data', description, input parameters schema (masterId as required string), used in the MCP tool configuration.
      type: 'function',
      function: {
        name: 'get_test_run_errors_data',
        description: 'Get the errors report data for a specified test run (master).',
        parameters: {
          type: 'object',
          properties: {
            masterId: {
              type: 'string',
              description: 'The ID of the test run (master) to retrieve the errors report data for.'
            }
          },
          required: ['masterId']
        }
      }
    }
  • lib/tools.js:7-16 (registration)
    The discoverTools function that dynamically imports and registers all tools listed in toolPaths, including this one by loading its apiTool export.
    export async function discoverTools() {
      const toolPromises = toolPaths.map(async (file) => {
        const module = await import(`../tools/${file}`);
        return {
          ...module.apiTool,
          path: file,
        };
      });
      return Promise.all(toolPromises);
    }
  • tools/paths.js:7-7 (registration)
    The path to this tool's file listed in toolPaths array, enabling its discovery and registration.
    'blazemeter/new-collection/get-test-run-errors-data.js',
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'Get[s]' data, implying a read-only operation, but doesn't clarify aspects like whether it requires authentication, has rate limits, returns paginated results, or what format the errors data is in (e.g., structured JSON, raw logs). This leaves significant gaps for an agent to understand how to handle the tool effectively.

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 that directly states the tool's purpose without any wasted words. It is front-loaded with the core action and resource, making it easy to parse quickly. Every part of the sentence contributes essential information.

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 the complexity of retrieving errors data (which could involve detailed reports or logs), the lack of annotations and output schema means the description is incomplete. It doesn't explain what the returned data looks like (e.g., error messages, counts, timestamps) or any behavioral traits like error handling. This makes it inadequate for an agent to fully understand the tool's context and usage.

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?

The input schema has 100% description coverage, with the 'masterId' parameter clearly documented as 'The ID of the test run (master) to retrieve the errors report data for.' The description adds no additional meaning beyond this, such as examples of valid IDs or context on where to find them. Given the high schema coverage, a baseline score of 3 is appropriate, as 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 action ('Get') and the resource ('errors report data for a specified test run'), making the purpose understandable. However, it doesn't differentiate this tool from sibling tools like 'get_test_run_summary' or 'get_test_run_aggregate_data', which might also retrieve test run data but for different aspects.

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 mentions 'errors report data' but doesn't specify scenarios where this is preferred over other test run data tools, such as for debugging failures or monitoring error trends, leaving the agent to infer usage from the name 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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