How to integrate Blazemeter MCP with LlamaIndex

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Introduction

This guide walks you through connecting Blazemeter to LlamaIndex 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 LlamaIndex 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:
  • Set your OpenAI and Composio API keys
  • Install LlamaIndex and Composio packages
  • Create a Composio Tool Router session for Blazemeter
  • Connect LlamaIndex to the Blazemeter MCP server
  • Build a Blazemeter-powered agent using LlamaIndex
  • Interact with Blazemeter through natural language

What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.

Key features include:

  • ReAct Agent: Reasoning and acting pattern for tool-using agents
  • MCP Tools: Native support for Model Context Protocol
  • Context Management: Maintain conversation context across interactions
  • Async Support: Built 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 you begin, make sure you have:
  • Python 3.8/Node 16 or higher installed
  • A Composio account with the API key
  • An OpenAI API key
  • A Blazemeter account and project
  • Basic familiarity with async Python/Typescript

Getting API Keys for OpenAI, Composio, and Blazemeter

OpenAI API key (OPENAI_API_KEY)
  • Go to the OpenAI dashboard
  • Create an API key if you don't have one
  • Assign it to OPENAI_API_KEY in .env
Composio API key and user ID
  • Log into the Composio dashboard
  • Copy your API key from Settings
    • Use this as COMPOSIO_API_KEY
  • Pick a stable user identifier (email or ID)
    • Use this as COMPOSIO_USER_ID

Installing dependencies

pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv

Create a new Python project and install the necessary dependencies:

  • composio-llamaindex: Composio's LlamaIndex integration
  • llama-index: Core LlamaIndex framework
  • llama-index-llms-openai: OpenAI LLM integration
  • llama-index-tools-mcp: MCP client for LlamaIndex
  • python-dotenv: Environment variable management

Set environment variables

bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id

Create a .env file in your project root:

These credentials will be used to:

  • Authenticate with OpenAI's GPT-5 model
  • Connect to Composio's Tool Router
  • Identify your Composio user session for Blazemeter access

Import modules

import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

Create a new file called blazemeter_llamaindex_agent.py and import the required modules:

Key imports:

  • asyncio: For async/await support
  • Composio: Main client for Composio services
  • LlamaIndexProvider: Adapts Composio tools for LlamaIndex
  • ReActAgent: LlamaIndex's reasoning and action agent
  • BasicMCPClient: Connects to MCP endpoints
  • McpToolSpec: Converts MCP tools to LlamaIndex format

Load environment variables and initialize Composio

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")

What's happening:

This ensures missing credentials cause early, clear errors before the agent attempts to initialise.

Create a Tool Router session and build the agent function

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["blazemeter"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Blazemeter actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Blazemeter actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)

What's happening here:

  • We create a Composio client using your API key and configure it with the LlamaIndex provider
  • We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, blazemeter)
  • The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
  • LlamaIndex will connect to this endpoint to dynamically discover and use the available Blazemeter tools.
  • The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.

Create an interactive chat loop

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

What's happening here:

  • We're creating a direct terminal interface to chat with your Blazemeter database
  • The LLM's responses are streamed to the CLI for faster interaction.
  • The agent uses context to maintain conversation history
  • You can type 'quit' or 'exit' to stop the chat loop gracefully
  • Agent responses and any errors are displayed in a clear, readable format

Define the main entry point

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

What's happening here:

  • We're orchestrating the entire application flow
  • The agent gets built with proper error handling
  • Then we kick off the interactive chat loop so you can start talking to Blazemeter

Run the agent

npx ts-node llamaindex-agent.ts

When prompted, authenticate and authorise your agent with Blazemeter, then start asking questions.

Complete Code

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

import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["blazemeter"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Blazemeter actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Blazemeter actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

Conclusion

You've successfully connected Blazemeter to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Blazemeter tools through an MCP endpoint
  • LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
  • The agent becomes more capable without increasing prompt size
  • Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

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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 LlamaIndex?

Yes, you can. LlamaIndex 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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