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pbandreddy

LoadRunner Cloud MCP Server

by pbandreddy

projects_getLoadTestScripts

Retrieve load test scripts from a specific project in LoadRunner Cloud to analyze performance testing configurations and workflows.

Instructions

Retrieve scripts for a load test in a project from LoadRunner Cloud.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesThe ID of the project.
loadTestIdYesThe ID of the load test.

Implementation Reference

  • The handler function that makes an authenticated GET request to the LoadRunner Cloud API to retrieve scripts for the specified load test in the project.
    const executeFunction = async ({ projectId, loadTestId }) => {
      const baseUrl = process.env.LRC_BASE_URL;
      const tenantId = process.env.LRC_TENANT_ID;
      const token = await getAuthToken();
      try {
        // Construct the URL with query parameters
        const url = new URL(`${baseUrl}/projects/${projectId}/load-tests/${loadTestId}/scripts`);
        url.searchParams.append('TENANTID', tenantId);
    
        // Set up headers for the request
        const headers = {
          'Content-Type': 'application/json',
          'Authorization': `Bearer ${token}`
        };
    
        // Perform the fetch request
        const response = await fetch(url.toString(), {
          method: 'GET',
          headers
        });
    
        // Check if the response was successful
        if (!response.ok) {
          const text = await response.text();
          try {
            const errorData = JSON.parse(text);
            throw new Error(JSON.stringify(errorData));
          } catch (jsonErr) {
            // Not JSON, log the raw text
            console.error('Non-JSON error response:', text);
            throw new Error(text);
          }
        }
    
        // Parse and return the response data
        const text = await response.text();
        try {
          const data = JSON.parse(text);
          return data;
        } catch (jsonErr) {
          // Not JSON, log the raw text
          console.error('Non-JSON success response:', text);
          return { error: 'Received non-JSON response from API', raw: text };
        }
      } catch (error) {
        console.error('Error retrieving load test scripts:', error);
        return { error: 'An error occurred while retrieving load test scripts.' };
      }
    };
  • The tool schema defining the name, description, and input parameters (projectId and loadTestId as required strings).
    function: {
      name: 'projects_getLoadTestScripts',
      description: 'Retrieve scripts for a load test in a project from LoadRunner Cloud.',
      parameters: {
        type: 'object',
        properties: {
          projectId: {
            type: 'string',
            description: 'The ID of the project.'
          },
          loadTestId: {
            type: 'string',
            description: 'The ID of the load test.'
          }
        },
        required: ['projectId', 'loadTestId']
      }
    }
  • tools/paths.js:1-11 (registration)
    The toolPaths array includes the path to this tool's definition file, enabling its dynamic discovery and registration.
    export const toolPaths = [
      'loadrunner-cloud/load-runner-cloud-api/projects-get-projects.js',
      'loadrunner-cloud/load-runner-cloud-api/test-runs-get-active-test-runs.js',
      'loadrunner-cloud/load-runner-cloud-api/test-runs-get-test-run-transactions.js',
      'loadrunner-cloud/load-runner-cloud-api/test-runs-get-test-run-summary.js',
      'loadrunner-cloud/load-runner-cloud-api/test-runs-get-http-responses.js',
      'loadrunner-cloud/load-runner-cloud-api/test-runs-get-test-run-recent.js',
      'loadrunner-cloud/load-runner-cloud-api/projects-get-load-tests.js',
      'loadrunner-cloud/load-runner-cloud-api/projects-get-load-test-scripts.js',
      'loadrunner-cloud/load-runner-cloud-api/projects-get-load-test-runs.js'
    ];
  • lib/tools.js:7-16 (registration)
    The discoverTools function dynamically imports the apiTool object from each file in toolPaths, registering all tools including projects_getLoadTestScripts.
    export async function discoverTools() {
      const toolPromises = toolPaths.map(async (file) => {
        const module = await import(`../tools/${file}`);
        return {
          ...module.apiTool,
          path: file,
        };
      });
      return Promise.all(toolPromises);
    }
  • Uses getAuthToken helper (imported from auth-get-token.js) to obtain authentication token for API requests.
    const executeFunction = async ({ projectId, loadTestId }) => {
      const baseUrl = process.env.LRC_BASE_URL;
      const tenantId = process.env.LRC_TENANT_ID;
      const token = await getAuthToken();
      try {
        // Construct the URL with query parameters
        const url = new URL(`${baseUrl}/projects/${projectId}/load-tests/${loadTestId}/scripts`);
        url.searchParams.append('TENANTID', tenantId);
    
        // Set up headers for the request
        const headers = {
          'Content-Type': 'application/json',
          'Authorization': `Bearer ${token}`
        };
    
        // Perform the fetch request
        const response = await fetch(url.toString(), {
          method: 'GET',
          headers
        });
    
        // Check if the response was successful
        if (!response.ok) {
          const text = await response.text();
          try {
            const errorData = JSON.parse(text);
            throw new Error(JSON.stringify(errorData));
          } catch (jsonErr) {
            // Not JSON, log the raw text
            console.error('Non-JSON error response:', text);
            throw new Error(text);
          }
        }
    
        // Parse and return the response data
        const text = await response.text();
        try {
          const data = JSON.parse(text);
          return data;
        } catch (jsonErr) {
          // Not JSON, log the raw text
          console.error('Non-JSON success response:', text);
          return { error: 'Received non-JSON response from API', raw: text };
        }
Behavior2/5

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

With no annotations, the description carries the full burden but provides minimal behavioral insight. It implies a read-only operation ('Retrieve'), but doesn't disclose permissions, rate limits, pagination, error handling, or output format. This is inadequate 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 a single, efficient sentence that front-loads the core purpose. It avoids redundancy and wastes no words, though it could be slightly more structured (e.g., by hinting at output).

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, no output schema, and a read-oriented tool, the description is incomplete. It lacks details on what 'scripts' entail (e.g., file types, content), how results are returned, or any behavioral traits, leaving significant gaps for the agent.

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 (projectId and loadTestId). The description adds no additional meaning beyond what's in the schema, such as format examples or relationships between parameters, meeting the baseline for high coverage.

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 ('Retrieve') and the resource ('scripts for a load test in a project'), specifying the source ('from LoadRunner Cloud'). It distinguishes from siblings like 'projects_getLoadTests' (which likely lists tests) or 'test_runs_getTestRunTransactions' (which focuses on transactions), but doesn't explicitly contrast them.

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. It doesn't mention prerequisites (e.g., needing a valid project and load test), exclusions, or comparisons to siblings like 'projects_getLoadTestRuns' or 'test_runs_getHttpResponses', leaving the agent to infer context.

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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