How to integrate Blazemeter MCP with Pydantic AI

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Introduction

This guide walks you through connecting Blazemeter to Pydantic AI 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 Pydantic AI 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

TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Blazemeter
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Blazemeter workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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.
Register UserTool to register a new user account in BlazeMeter.
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:

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

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming

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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Blazemeter
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Blazemeter
  • MCPServerStreamableHTTP connects to the Blazemeter MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Blazemeter
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["blazemeter"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to Blazemeter tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
blazemeter_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[blazemeter_mcp],
    instructions=(
        "You are a Blazemeter assistant. Use Blazemeter tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Blazemeter endpoint
  • The agent uses GPT-5 to interpret user commands and perform Blazemeter operations
  • The instructions field defines the agent's role and behavior

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Blazemeter.\n")

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", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Blazemeter API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

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

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Blazemeter
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["blazemeter"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    blazemeter_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[blazemeter_mcp],
        instructions=(
            "You are a Blazemeter assistant. Use Blazemeter tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Blazemeter.\n")

    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", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

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

Conclusion

You've built a Pydantic AI agent that can interact with Blazemeter through Composio's Tool Router. With this setup, your agent can perform real Blazemeter actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Blazemeter for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

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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 Pydantic AI?

Yes, you can. Pydantic AI 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.

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