BlazeMeter MCP Server
Provides tools for accessing BlazeMeter's performance testing API, enabling retrieval of test data, workspace and project management, test run analysis, aggregate reports, error reports, and performance metrics monitoring.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@BlazeMeter MCP Server show me the latest test run results"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
BlazeMeter MCP Server
This project provides a Model Context Provider (MCP) server for integrating with BlazeMeter's API, enabling programmatic access to performance test data and management features. The server exposes a set of tools that can be used by MCP-compatible clients (such as Claude Desktop and Cursor) to interact with BlazeMeter resources.
Let's set things up!
🚦 Getting Started
⚙️ Prerequisites
Before starting, please ensure you have:
npm (included with Node)
Warning: if you run with a lower version of Node, fetch won't be present. Tools use fetch to make HTTP calls. To work around this, you can modify the tools to use node-fetch instead. Make sure that node-fetch is installed as a dependency and then import it as fetch into each tool file.
📥 Installation & Setup
1. Install dependencies
Run from your project's root directory:
npm installOn Linux/macOS (sh):
which nodeOn Windows (PowerShell):
Get-Command node | Select-Object -ExpandProperty Source
To check the node version, run:
node --versionTo get the absolute path to mcpServer.js, run:
On Linux/macOS (sh):
realpath mcpServer.jsOn Windows (PowerShell):
Resolve-Path mcpServer.js | Select-Object -ExpandProperty Path
Related MCP server: JMeter MCP Server
👩💻 Connect the MCP Server to Claude Desktop or Cursor
You can connect your MCP server to any MCP client. Below are instructions for connecting it to Claude Desktop and Cursor.
Claude Desktop
Step 1: Note the full path to node and the mcpServer.js from the previous step.
Step 2. Open Claude Desktop → Settings → Developers → Edit Config and add a new MCP server:
{
"mcpServers": {
"<server_name>": {
"command": "<absolute/path/to/node>",
"args": ["<absolute/path/to/mcpServer.js>"]
}
}
}Restart Claude Desktop to activate this change. Make sure the new MCP is turned on and has a green circle next to it. If so, you're ready to begin a chat session that can use the tools you've connected.
Cursor
Step 1: Note the full path to node and the mcpServer.js from the previous step.
Step 2. In Cursor, open the Command Palette and search for "MCP: Add Server" or go to Settings → MCP Servers.
Step 3. Add a new MCP server with the following configuration:
Command:
<absolute/path/to/node>Arguments:
<absolute/path/to/mcpServer.js>
Step 4. Save and enable the server. Cursor will show the MCP server as available, and you can use the BlazeMeter tools directly from the Cursor interface.
Note: For both clients, ensure you use the absolute paths and Node.js v18+.
Warning: If you don't supply an absolute path to a node version that is v18+, the client may fall back to another node version on the system of a previous version. In this case, the fetch API won't be present and tool calls will not work. If that happens, you can a) install a newer version of node and point to it in the command, or b) import node-fetch into each tool as fetch, making sure to also add the node-fetch dependency to your package.json.
Additional Options
🐳 Docker Deployment (Production)
For production deployments, you can use Docker:
1. Build Docker image
docker build -t <your_server_name> .2. Client Integration
Add Docker server configuration to your MCP client (Claude Desktop or Cursor):
{
"mcpServers": {
"<your_server_name>": {
"command": "docker",
"args": ["run", "-i", "--rm", "--env-file=.env", "<your_server_name>"]
}
}
}Add your environment variables (API keys, etc.) inside the
.envfile.
The project comes bundled with the following minimal Docker setup:
FROM node:22.12-alpine AS builder
WORKDIR /app
COPY package.json package-lock.json ./
RUN npm install
COPY . .
ENTRYPOINT ["node", "mcpServer.js"]🌐 Server-Sent Events (SSE)
To run the server with Server-Sent Events (SSE) support, use the --sse flag:
node mcpServer.js --sse🛠️ Additional CLI commands
List tools
List descriptions and parameters from all generated tools with:
node index.js toolsExample:
Available Tools:
Workspace: acme-workspace
Collection: useful-api
list_all_customers
Description: Retrieve a list of useful things.
Parameters:
- magic: The required magic power
- limit: Number of results returned
[...additional parameters...]🔥 BlazeMeter API Tools
This project includes tools for interacting with the BlazeMeter API. You must set the following environment variables in your .env file:
Example .env
BASE_URL=https://a.blazemeter.com
BZM_USERNAME=your_blazemeter_api_key
BZM_PASSWORD=your_blazemeter_api_secret
BZM_ACCOUNT_ID=your_blazemeter_account_id # (optional, used by workspace-list)
BZM_WORKSPACE_ID=your_blazemeter_workspace_id # (optional, used by project-list)For tools where the parameter is optional, the value will be read from
.envif not provided.For tools where the parameter is required, you must provide it in the request.
Supported BlazeMeter Endpoints
Tool Name | Endpoint & Description | Required Parameter(s) |
get_workspaces |
| (optional) accountId |
get_projects |
| (optional) workspaceId |
get_test_runs |
| testId |
get_test_run_summary |
| masterId |
get_test_run_aggregate_data |
| masterId |
get_test_run_errors_data |
| masterId |
get_test_run_thresholds |
| masterId |
get_test_run_timeline_kpis |
| masterId |
Available Tools
8 toolsget_projectsC
Get projects from a specified workspace.
Inputs: workspaceId.
get_test_run_aggregate_dataC
Get the aggregate report data for a specified test run (master).
Inputs: masterId (required).
get_test_run_errors_dataC
Get the errors report data for a specified test run (master).
Inputs: masterId (required).
get_test_runsC
Get test runs (masters) for a specified test.
Inputs: testId (required).
get_test_run_summaryC
Get the summary report for a specified test run (master).
Inputs: masterId (required).
get_test_run_thresholdsC
Get the thresholds report for a specified test run (master).
Inputs: masterId (required).
get_test_run_timeline_kpisB
Get the timeline KPIs report for a specified test run (master).
Inputs: masterId (required).
get_workspacesC
Get workspaces from a specified account.
Inputs: accountId.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 8 tools
Every tool has a clearly distinct purpose targeting specific resources and report types. The six test run report tools (aggregate_data, errors_data, summary, thresholds, timeline_kpis) each retrieve different data slices without overlap, while get_projects and get_workspaces handle distinct workspace and account-level operations.
All tools follow a consistent verb_noun pattern with 'get_' prefix and snake_case naming. The naming structure is perfectly predictable: get_[resource]_[optional_specific_data] (e.g., get_test_run_aggregate_data, get_workspaces).
Eight tools is reasonable for a performance testing domain, though slightly thin for complete lifecycle coverage. The tools focus heavily on retrieval operations for test runs and workspaces, which fits the server's apparent monitoring/reporting purpose but might benefit from additional test execution or configuration management tools.
The surface provides excellent read-only coverage for test run reports and workspace/project retrieval, but has notable gaps in test creation, execution, and management operations. Agents can query existing data but cannot initiate tests, modify configurations, or perform other essential performance testing workflow actions.
Maintenance
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