BlazeMeter Performance Test MCP server

The BlazeMeter Performance Test MCP Server connects AI tools directly to cloud-based BlazeMeter Performance testing platform. It enables AI assistants, agents, and chat-based tools to interact with BlazeMeter performance tests through the Model Context Protocol (MCP). 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.

For related BlazeMeter MCP servers, see also Service Virtualization MCP server and API Test MCP server.

What you can do with the BlazeMeter Performance Test MCP server

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.

See BlazeMeter MCP server use cases.

  • 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.

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Install BlazeMeter MCP Server

For details on installation and configuration, see the README documentation at https://github.com/Blazemeter/bzm-mcp/.

You can deploy BlazeMeter MCP Server locally.

Installation options:

  • Installation using our interactive CLI tool

  • Manual client configuration

    • Binary installation

    • from remote source code

  • Docker MCP Client Configuration

Prerequisites:

  • BlazeMeter API credentials: API Key ID and Secret.

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

  • (Only for Docker-based deployment:) Docker

  • (Only for installation from source code distribution:) uv (a high-performance Python package) and Python 3.11+.

  • BlazeMeter's AI-assisted features require account owner consent. For more information, see Manage AI Consent.