Skip to main content
Glama
pbandreddy

LoadRunner Cloud MCP Server

by pbandreddy

test_runs_getHttpResponses

Retrieve HTTP response data from LoadRunner Cloud performance tests to analyze server behavior and identify issues during test execution.

Instructions

Get HTTP responses for a test run from LoadRunner Cloud.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
runIdYesThe ID of the test run.

Implementation Reference

  • The main execution function that handles the tool logic: authenticates, constructs the API URL, fetches HTTP responses from LoadRunner Cloud for the given runId, and parses the JSON response.
    const executeFunction = async ({ runId }) => {
      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(`${baseUrl}/test-runs/${runId}/http-responses`);
        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 HTTP responses:', error);
        return { error: 'An error occurred while retrieving HTTP responses.' };
      }
    };
  • The tool's JSON Schema definition, including name, description, input parameters (runId: string, required), used for validation and listing.
      type: 'function',
      function: {
        name: 'test_runs_getHttpResponses',
        description: 'Get HTTP responses for a test run from LoadRunner Cloud.',
        parameters: {
          type: 'object',
          properties: {
            runId: {
              type: 'string',
              description: 'The ID of the test run.'
            }
          },
          required: ['runId']
        }
      }
    }
  • lib/tools.js:7-16 (registration)
    Discovers and loads the apiTool objects from all tool files listed in toolPaths, including this tool, making them available for the MCP server.
    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:1-11 (registration)
    Central list of all tool file paths relative to tools/, explicitly including the path to this tool's implementation file for discovery.
    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'
    ];
  • Supporting helper function getAuthToken() used by the handler for authentication. (Note: excerpt shows usage; full helper file provides the auth logic.)
    /**
     * Function to get an auth token from LoadRunner Cloud.
     *
     * @returns {Promise<string|Object>} - The access token or an error message object.
     */
    const getAuthToken = async () => {
      const baseUrl = process.env.LRC_BASE_URL;
      const tenantId = process.env.LRC_TENANT_ID;
      const clientId = process.env.LRC_CLIENT_ID;
      const clientSecret = process.env.LRC_CLIENT_SECRET;
    
      try {
        const url = new URL(`${baseUrl}/auth-client`);
        url.searchParams.append('TENANTID', tenantId);
    
        const headers = {
          'Content-Type': 'application/json',
          'accept': 'application/json'
        };
    
        const body = JSON.stringify({
          client_id: clientId,
          client_secret: clientSecret
        });
    
        const response = await fetch(url.toString(), {
          method: 'POST',
          headers,
          body
        });
    
        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);
          }
        }
    
        const data = await response.json();
        // Adjust according to actual API response structure
        return data.access_token || data.token || data;
      } catch (error) {
        console.error('Error retrieving auth token:', error);
        return { error: 'An error occurred while retrieving auth token.' };
      }
    };
    
    export { getAuthToken }; 
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves HTTP responses but doesn't describe what the responses include (e.g., status codes, headers, body), how they are formatted, pagination, rate limits, or authentication needs. This leaves significant gaps for a tool that likely returns complex data.

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, clear sentence with zero waste. It is appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration, making it highly efficient.

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 HTTP responses (which could involve detailed data like status codes, headers, and body), the lack of annotations and output schema, and the description's minimal detail, this is incomplete. The agent would struggle to understand the full behavior and output without additional context.

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 single parameter 'runId' documented as 'The ID of the test run.' The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline score of 3 for high schema coverage without extra value.

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 HTTP responses') and resource ('for a test run from LoadRunner Cloud'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'test_runs_getTestRunResults' or 'test_runs_getTestRunTransactions', 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 doesn't mention prerequisites (e.g., needing a valid runId), exclusions, or comparisons to sibling tools like 'test_runs_getTestRunResults', leaving the agent to infer usage context from the tool name alone.

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/pbandreddy/loadrunner-cloud-mcp-server'

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