Blazemeter with AutoGen

How to integrate Blazemeter MCP with Autogen

Trusted by

GET STARTED FOR FREE GET A DEMO

30 min · no commitment · see it on your stack

Introduction Also integrate Blazemeter with TL;DR What is AutoGen What is the Blazemeter MCP server Supported Tools & Triggers Creating MCP Server - Stand-alone vs Composio SDK Step-by-step Guide Complete Code Conclusion How to build Blazemeter MCP Agent with another framework Explore Other Toolkits FAQ

Connect Blazemeter without Auth hassles

We manage OAuth, API Key, token refresh, and scopes, you just build.

Try for Free

Introduction

This guide walks you through connecting Blazemeter to AutoGen using the Composio tool router. By the end, you'll have a working Blazemeter agent that can start a new performance test on your main project, fetch results from the latest test run, list all test runs for project alpha through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a Blazemeter account through Composio's Blazemeter MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Blazemeter with

OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenClaw Hermes CLI Google ADK LangChain Vercel AI SDK Mastra AI LlamaIndex CrewAI

TL;DR

Here's what you'll learn:

Get and set up your OpenAI and Composio API keys
Install the required dependencies for Autogen and Composio
Initialize Composio and create a Tool Router session for Blazemeter
Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
Configure an Autogen AssistantAgent that can call Blazemeter tools
Run a live chat loop where you ask the agent to perform Blazemeter operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

Multi-Agent Systems: Build collaborative agent workflows
MCP Workbench: Native support for Model Context Protocol tools
Streaming HTTP: Connect to external services through streamable HTTP
AssistantAgent: Pre-built agent class for tool-using assistants

What is the Blazemeter MCP server, and what's possible with it?

The Blazemeter MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Blazemeter account. It provides structured and secure access so your agent can perform Blazemeter operations on your behalf.

Supported Tools & Triggers

Tools

Convert TransactionsTool to convert transaction files to BlazeMeter DSL format for service virtualization.

Create API Monitoring ScheduleTool to create a new schedule for running API monitoring tests.

Create Multi TestTool to create a new multi-test within a specified project.

Create Private LocationTool to create a new private location in BlazeMeter.

Create Private Location AgentCreates a new agent (server) within a BlazeMeter private location.

Create ProjectCreates a new project within a BlazeMeter workspace.

Create SearchExecute a search query against BlazeMeter entities using advanced filtering and sorting.

Create TagCreates a new tag in BlazeMeter for organizing and categorizing resources.

Create TestTool to create a new single test within a specified project.

Create Workspace AssetTool to create an asset in a workspace for test data management.

Create Asset DependencyTool to create a dependency relationship between two assets in a BlazeMeter workspace.

Create Workspace PackageCreates a new package within a BlazeMeter workspace.

Create Workspace TransactionsTool to create transactions in a BlazeMeter workspace for service virtualization.

Delete API Monitoring ScheduleTool to delete a specific test schedule by its ID.

Delete Private Location WorkspaceTool to remove a workspace from a private location.

Delete ProjectTool to delete a specific project by its ID.

Delete Test FileTool to delete a file from a test.

Delete TestsTool to delete a test by its ID.

Delete Workspace Asset DependencyTool to delete a dependency from a workspace's asset repository by its ID.

Delete Workspace AssetTool to delete an asset from a workspace in BlazeMeter's Asset Repository.

Delete Workspace Assets DependenciesTool to delete asset dependencies by source/target in a workspace.

Delete Workspace LogsTool to delete master test execution logs from a BlazeMeter workspace.

Delete Workspace ManagersTool to remove managers from a workspace.

Delete Workspace PackageTool to delete a package from a workspace in the BlazeMeter Asset Repository.

Duplicate TestTool to duplicate an existing test by its ID.

Export PackageTool to export a package from BlazeMeter Asset Repository as a zip file.

Export Workspaces PackagesTool to export multiple packages from a workspace as a zip file.

Generate Test Data from Data ModelTool to generate test data from a data model in Asset Repository.

Generate Workspace Test DataTool to generate synthetic test data on-the-fly without storing in Asset Repository.

Get AccountsTool to retrieve a list of accounts associated with the authenticated user.

Get API Monitoring ScheduleTool to retrieve details of a specific API monitoring schedule by its ID.

Get API Monitoring SchedulesRetrieves a paginated list of API monitoring test schedules.

Get Generator FunctionsTool to retrieve all available test data generator functions from BlazeMeter Test Data API.

Get Generator Seed ListsTool to retrieve a list of all available seed lists from BlazeMeter Test Data Management API.

Get Info HealthTool to retrieve the BlazeMeter service health status.

Get Info VersionTool to retrieve BlazeMeter service version information.

Get Masters Reports Main SummaryTool to retrieve request statistics summary for a master test run.

Get Multi TestTool to retrieve details of a specific multi-test.

Get Multi TestsRetrieves a paginated list of multi-tests within a BlazeMeter workspace.

Get Private LocationsTool to retrieve a list of private locations filtered by account or workspace.

Get Project DetailsTool to retrieve detailed information about a specific project by its ID.

Get ProjectsTool to retrieve a list of projects within a specified workspace.

Get RegionsTool to retrieve a list of all available test regions for API monitoring.

Get Search MetadataRetrieve metadata about searchable entities, fields, relationships, and operators in BlazeMeter's search API.

Get Shared FoldersTool to retrieve a list of shared folders within a specified workspace.

Get TagsTool to retrieve a list of all tags from BlazeMeter Mock Services API.

Get Test DetailsTool to retrieve complete details of a specific test by its ID.

Get TestsRetrieve a list of performance tests filtered by workspace or project.

Get Tests FilesTool to list all files associated with a test.

Get Test ValidationsTool to retrieve validation results for a specific test by its ID.

Get UserRetrieve the authenticated user's profile information including their default project and preferences.

Get User Active SessionsTool to retrieve the list of active test sessions for the authenticated user.

Get User InvitesTool to retrieve pending invites for the authenticated user.

Get User ProjectsTool to retrieve all projects belonging to the authenticated user.

Get Workspace DetailsTool to retrieve detailed information about a specific workspace by its ID.

Get Workspace PackageTool to retrieve a specific package by its ID from a workspace in the BlazeMeter Asset Repository.

Get WorkspacesTool to retrieve a list of workspaces for a specified account.

Get Workspace AssetsTool to retrieve all data models (assets) in a workspace for Test Data Management.

Get Workspace Asset By IDTool to retrieve a specific asset by ID from the Test Data Management Asset Repository.

Get Workspace Asset DataTool to retrieve data from a specific asset in a workspace's asset repository.

Get Workspace Assets DependenciesTool to retrieve all dependencies for a given workspace with optional filtering criteria.

Get Workspace Asset DependencyTool to retrieve a specific dependency by ID from a workspace's asset repository.

Get Asset DependenciesTool to retrieve dependencies for a specific asset in a workspace from the BlazeMeter Asset Repository.

Get Workspace Data Model By IDTool to retrieve a specific data model by ID from a workspace in Test Data Management.

Get Virtual Service Template by IDTool to get virtual service template details from a specific workspace.

Get Workspace PackagesTool to retrieve packages from a BlazeMeter workspace.

Get Workspace Package DependenciesTool to retrieve package dependencies for a specific package in a workspace.

Get Workspace Service Mock TemplatesTool to list virtual service templates available in a workspace.

Get Workspace TransactionsTool to list transactions for virtual services in a workspace.

Get Workspace UsersTool to retrieve a list of users within a specified workspace.

Import Workspace PackageImport a package from a ZIP file into a BlazeMeter workspace.

List Generator Card IssuersTool to retrieve a list of available card issuers for test data generation.

Publish API DataPublishes test data through the BlazeMeter Test Data Management API.

Start TestTool to start a preconfigured performance load test.

Stop MasterGracefully stop a running BlazeMeter test execution (master) by its ID.

Stop TestTool to stop all active masters (test executions) for a given test ID.

Terminate User Active SessionsTool to immediately terminate active user sessions in BlazeMeter.

Terminate Workspaces MastersTool to terminate all running masters in a BlazeMeter workspace.

Update API Monitoring ScheduleTool to update the configuration of an existing API monitoring schedule.

Update ProjectTool to update an existing BlazeMeter project by its ID.

Update TestTool to update details of a specific test by its ID.

Update Workspace AssetTool to update an existing asset in a BlazeMeter workspace.

Update Workspaces Assets DependenciesTool to update asset dependencies in a BlazeMeter workspace.

Update Workspace PackageTool to update an existing package in a BlazeMeter workspace.

Update Workspace Package DependenciesTool to update package dependencies for a specific package in a workspace.

Update Workspace Service Mock TemplateTool to update a virtual service template configuration (Service Virtualization).

Update Workspace UserTool to update a user's role and status within a BlazeMeter workspace.

Upload Test FilesUpload a file asset (script, data file, or configuration) to a BlazeMeter test.

Upload Workspace Asset DataTool to upload asset data to a BlazeMeter workspace.

Validate TestTool to validate a specific test by its ID.

Validate Workspace AssetTool to validate a data model asset in a workspace for test data management.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

You will need:

A Composio API key
An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
A Blazemeter account you can connect to Composio
Some basic familiarity with Autogen and Python async

Getting API Keys for OpenAI and Composio

OpenAI API Key

Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
Keep the API key safe.

Composio API Key

Log in to the Composio dashboard.
Navigate to your API settings and generate a new API key.
Store this key securely as you'll need it for authentication.

Install dependencies

bash

pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

composio connects your agent to Blazemeter via MCP
autogen-agentchat provides the AssistantAgent class
autogen-ext-openai provides the OpenAI model client
autogen-ext-tools provides MCP workbench support

Set up environment variables

bash

COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

COMPOSIO_API_KEY is required to talk to Composio
OPENAI_API_KEY is used by Autogen's OpenAI client
USER_ID is how Composio identifies which user's Blazemeter connections to use

Import dependencies and create Tool Router session

python

import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Blazemeter session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["blazemeter"]
    )
    url = session.mcp.url

What's happening:

load_dotenv() reads your .env file
Composio(api_key=...) initializes the SDK
create(...) creates a Tool Router session that exposes Blazemeter tools
session.mcp.url is the MCP endpoint that Autogen will connect to

Configure MCP parameters for Autogen

python

# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

url points to the Tool Router MCP endpoint from Composio
timeout is the HTTP timeout for requests
sse_read_timeout controls how long to wait when streaming responses
terminate_on_close=True cleans up the MCP server process when the workbench is closed

Create the model client and agent

python

# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Blazemeter assistant agent with MCP tools
    agent = AssistantAgent(
        name="blazemeter_assistant",
        description="An AI assistant that helps with Blazemeter operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

OpenAIChatCompletionClient wraps the OpenAI model for Autogen
McpWorkbench connects the agent to the MCP tools
AssistantAgent is configured with the Blazemeter tools from the workbench

Run the interactive chat loop

python

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Blazemeter related question or task to the agent.\n")

# Conversation loop
while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

What's happening:

The script prompts you in a loop with You:
Autogen passes your input to the model, which decides which Blazemeter tools to call via MCP
agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Blazemeter and AutoGen:

python

import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Blazemeter session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["blazemeter"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Blazemeter assistant agent with MCP tools
        agent = AssistantAgent(
            name="blazemeter_assistant",
            description="An AI assistant that helps with Blazemeter operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Blazemeter related question or task to the agent.\n")

        # Conversation loop
        while True:
            user_input = input("You: ").strip()

            if user_input.lower() in ['exit', 'quit', 'bye']:
                print("\nGoodbye!")
                break

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You now have an Autogen assistant wired into Blazemeter through Composio's Tool Router and MCP. From here you can:

Add more toolkits to the toolkits list, for example notion or hubspot
Refine the agent description to point it at specific workflows
Wrap this script behind a UI, Slack bot, or internal tool

Once the pattern is clear for Blazemeter, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

How to build Blazemeter MCP Agent with another framework

OpenAI Agents SDK

Use Blazemeter MCP with OpenAI Agents SDK

Claude Agent SDK

Use Blazemeter MCP with Claude Agent SDK

Claude Code

Use Blazemeter MCP with Claude Code

Claude Cowork

Use Blazemeter MCP with Claude Cowork

Codex

Use Blazemeter MCP with Codex

OpenClaw

Use Blazemeter MCP with OpenClaw

Hermes

Use Blazemeter MCP with Hermes

CLI

Use Blazemeter MCP with CLI

Google ADK

Use Blazemeter MCP with Google ADK

LangChain

Use Blazemeter MCP with LangChain

Vercel AI SDK

Use Blazemeter MCP with Vercel AI SDK

Mastra AI

Use Blazemeter MCP with Mastra AI

LlamaIndex

Use Blazemeter MCP with LlamaIndex

CrewAI

Use Blazemeter MCP with CrewAI

Explore Other Toolkits

Supabase

Oauth2Api Key

Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. It lets developers build modern apps without managing infrastructure.

Codeinterpreter

No Auth

Codeinterpreter is a Python-based coding environment with built-in data analysis and visualization. It lets you instantly run scripts, plot results, and prototype solutions inside supported platforms.

GitHub

Oauth2

GitHub is a code hosting platform for version control and collaborative software development. It streamlines project management, code review, and team workflows in one place.

TOOLKIT MARKETPLACE

FAQ

What are the differences in Tool Router MCP and Blazemeter MCP?

With a standalone Blazemeter MCP server, the agents and LLMs can only access a fixed set of Blazemeter tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Blazemeter and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with Autogen?

Yes, you can. Autogen fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Blazemeter tools.

Can I manage the permissions and scopes for Blazemeter while using Tool Router?

Yes, absolutely. You can configure which Blazemeter scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Blazemeter data and credentials are handled as safely as possible.

Used by agents from

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.

Get started for free Get a demo↗

Harsha GaddipatiCo-founder, Slashy

Karan skipped his own birthday party to fix our critical issue. It was 10 pm and he diverted his Waymo to help us instead. This really sets the bar, shows you the commitment you need to have when users rely on your software.

Abhi AryaCo-founder, Opennote

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it has immensely helped in keeping new users on the platform.

Nirman DaveCEO, Zams

We chose Composio over Pipedream because it delivered depth where it mattered. It supported niche tools and tricky edge cases that other platforms simply ignored. Giving us confidence to scale without compromising.

Ryan YuFounder, Extra Thursday

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down in the complexities of managing agent auth would have been a death sentence for Extra Thursday.

Tomisin JenrolaFounder & CEO, SwarmZero

Before partnering with Composio, adding tool integrations was a slow, resource-intensive process. Each integration could take weeks or months of engineering time, and maintaining them meant constantly keeping up with API changes.

Jerome LeclancheCo-Founder, Ingram Technologies

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Harsha GaddipatiCo-founder, Slashy

Abhi AryaCo-founder, Opennote

Nirman DaveCEO, Zams

Ryan YuFounder, Extra Thursday

Tomisin JenrolaFounder & CEO, SwarmZero

Jerome LeclancheCo-Founder, Ingram Technologies

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Harsha GaddipatiCo-founder, Slashy

Abhi AryaCo-founder, Opennote

Nirman DaveCEO, Zams

Ryan YuFounder, Extra Thursday

Tomisin JenrolaFounder & CEO, SwarmZero

Jerome LeclancheCo-Founder, Ingram Technologies

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

How to integrate Blazemeter MCP with Autogen

Table of Contents

Connect Blazemeter without Auth hassles

Introduction

Also integrate Blazemeter with

TL;DR

What is AutoGen?

What is the Blazemeter MCP server, and what's possible with it?

Supported Tools & Triggers

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import dependencies and create Tool Router session

Configure MCP parameters for Autogen

Create the model client and agent

Run the interactive chat loop

Complete Code

Conclusion

How to build Blazemeter MCP Agent with another framework

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

OpenClaw

Hermes

CLI

Google ADK

LangChain

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

Explore Other Toolkits

Supabase

Codeinterpreter

GitHub

FAQ

What are the differences in Tool Router MCP and Blazemeter MCP?

Can I use Tool Router MCP with Autogen?

Can I manage the permissions and scopes for Blazemeter while using Tool Router?

How safe is my data with Composio Tool Router?

Used by agents from

Never worry about agent reliability