BlazeMeter MCP Server

MCP Server is a modular, extensible service that exposes tools, data, and workflows to AI models via the Model Context Protocol (MCP). It acts as a bridge between AI agents and real-world systems, enabling seamless interaction with APIs, databases, applications, and more.

The BlazeMeter MCP Server connects AI tools directly to BlazeMeter's cloud-based performance testing platform. This gives AI agents, assistants, and chatbots the ability to manage complete load testing workflows from creation to execution and reporting. All through natural language interactions.

Use cases

The BlazeMeter MCP Server is built for developers and QA teams who want to connect their AI tools to BlazeMeter's enterprise-grade performance testing capabilities, from simple test creation to complex multi-step automation workflows.

• Performance Test Management: Create, configure, and manage performance tests with automated script uploads and asset management.

• Test Execution & Monitoring: Start tests, monitor execution status, and retrieve comprehensive reports including summary, errors, and request statistics.

• Workspace & Project Organization: Navigate through accounts, workspaces, and projects to organize your testing infrastructure.

• Load Configuration: Configure test parameters including concurrency, iterations, duration, ramp-up settings, and geographic distribution.

• Report Analysis: Access detailed execution reports, error analysis, and performance metrics for comprehensive test insights.

• Account & Permission Management: Manage multiple accounts and workspaces with proper AI consent controls and permission validation.

Install BlazeMeter MCP Server

You can deploy BlazeMeter MCP Server locally.

Installation options:

• Installation using our interactive CLI tool

• Manual client configuration (Binary installation)

Prerequisites:

• BlazeMeter API credentials (API Key ID and Secret).

• Compatible MCP host (VS Code, Claude Desktop, Cursor, Windsurf, etc.)

• Docker (only for Docker-based deployment)

Use the CLI tool to set your MCP client

1. Get the BlazeMeter API credentials (API Key ID and Secret). For more information, see BlazeMeter API Keys.
   

   When downloading your API keys from BlazeMeter, save the api-keys.json file in the same folder where you'll place the MCP binary.
   

2. From the Releases page, download the appropriate binary file for your operating system. Select the binary that matches your OS (Windows, macOS, Linux).

3. Place the binary in the same folder as your api-keys.json file.

4. Execute or duble-click the binary to launch the interactive configuration tool.

The tool automatically generates the MCP JSON Key configuration for you.

Troubleshooting

For macOS, you may encounter a security alert "Apple could not verify 'bzm-mcp-macos' is free of malware."

To resolve this issue:

1. Go to System Settings, Privacy & Security, Security.

2. Locate the blocked application and click Allow Anyway.

3. Run the binary again.

Configure the client manually (Binary installation)

1. From the Releases page, download the binary for your operating system.

2. Configure your MCP client with the following settings:

{
  "mcpServers": {
    "BlazeMeter MCP": {
      "command": "/path/to/bzm-mcp-binary",
      "args": ["--mcp"],
      "env": {
        "BLAZEMETER_API_KEY": "/path/to/your/api-key.json"
      }
    }
  }
}

MCP Client Configuration for Docker

{
  "mcpServers": {
    "Docker BlazeMeter MCP": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "--mount",
        "type=bind,source=/path/to/your/test/files,target=/home/bzm-mcp/working_directory/",
        "-e",
        "API_KEY_ID=your_api_key_id",
        "-e",
        "API_KEY_SECRET=your_api_key_secret",
        "-e",
        "SOURCE_WORKING_DIRECTORY=/path/to/your/test/files",
        "ghcr.io/blazemeter/bzm-mcp:latest"
      ]
    }
  }
}

To get the API_KEY_ID and API_KEY_SECRET, see BlazeMeter API keys.