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How to integrate Piloterr MCP with Autogen

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Piloterr is a developer-first platform offering over 50 ready-to-use APIs for web scraping and data extraction. It helps businesses efficiently gather and integrate web data at scale.

12 Tools

Introduction

This guide walks you through connecting Piloterr to AutoGen using the Composio tool router. By the end, you'll have a working Piloterr agent that can run Google searches, fetch product info from retailers, list Google locations and languages, and check your usage through natural language commands.

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

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

Also integrate Piloterr with

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKGrok BotCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAIPydantic AI

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 Piloterr
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Piloterr tools
  • Run a live chat loop where you ask the agent to perform Piloterr 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 Piloterr MCP server, and what's possible with it?

The Piloterr MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Piloterr account. It provides structured and secure access to a suite of powerful web data extraction APIs, so your agent can perform actions like searching products, retrieving detailed product info, and monitoring account usage on your behalf.

  • Product search on retail platforms: Direct your agent to search for products on sites like Auchan or Bestbuy by keyword, category, or filters, and receive curated product listings.
  • Retrieve detailed product information: Ask your agent to fetch comprehensive product details—including company info—using specific product IDs from supported platforms.
  • Monitor account usage and credits: Let your agent check your Piloterr account usage and remaining credits, so you always know how much data access you have left.
  • Automated product data workflows: Enable your agent to seamlessly combine product search and retrieval, powering advanced e-commerce, analytics, or market research tasks.
  • Multi-platform product integration: Effortlessly access and aggregate product data from multiple online stores to inform business decisions or drive automation.

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

Step by step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Piloterr account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
2

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.
3

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 Piloterr via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

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 Piloterr connections to use
5

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 Piloterr session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["piloterr"]
    )
    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 Piloterr tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

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
7

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 Piloterr assistant agent with MCP tools
    agent = AssistantAgent(
        name="piloterr_assistant",
        description="An AI assistant that helps with Piloterr 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 Piloterr tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Piloterr 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 Piloterr 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 Piloterr 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 Piloterr session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["piloterr"]
    )
    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 Piloterr assistant agent with MCP tools
        agent = AssistantAgent(
            name="piloterr_assistant",
            description="An AI assistant that helps with Piloterr 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 Piloterr 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 Piloterr 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 Piloterr, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

Every Piloterr action and event your agent gets out of the box.

Auchan Product

Tool to retrieve detailed Auchan product information.

Auchan Product Search

Tool to search for products on Auchan by query or search URL.

Piloterr Get Product Info

Tool to retrieve detailed product information from G2.

List Chewy Products

Search Chewy products by product ID or title to retrieve product URLs and details.

List E.Leclerc Stores

Tool to find E.

List Google Countries

Tool to list available Google search countries.

List Google Languages

Tool to list available Google search languages filtered by query.

List Google Locations

Tool to list available Google search locations via Piloterr API.

List Leroy Merlin Products

Search Leroy Merlin products by name or identifier, returning product URLs and details.

List LinkedIn Industries

Tool to list LinkedIn industry codes from Piloterr API.

Piloterr Google Search

Tool to perform Google web search via Piloterr API.

Get Usage

Tool to get usage information and remaining credits for your Piloterr account.

FRAMEWORKS

How to build Piloterr MCP Agent with another framework

Claude Code logo

Claude Code

Use Piloterr MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Piloterr MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Piloterr MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Piloterr MCP with Claude Agent SDK

Grok Bot logo

Grok Bot

Use Piloterr MCP with Grok Bot

Codex logo

Codex

Use Piloterr MCP with Codex

OpenClaw logo

OpenClaw

Use Piloterr MCP with OpenClaw

Hermes logo

Hermes

Use Piloterr MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Piloterr MCP with Atomic Agent

Google ADK logo

Google ADK

Use Piloterr MCP with Google ADK

LangChain logo

LangChain

Use Piloterr MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Piloterr MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Piloterr MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Piloterr MCP with LlamaIndex

CrewAI logo

CrewAI

Use Piloterr MCP with CrewAI

Pydantic AI logo

Pydantic AI

Use Piloterr MCP with Pydantic AI

FAQ

Frequently asked questions

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

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 Piloterr tools.

Yes, absolutely. You can configure which Piloterr 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.

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 Piloterr data and credentials are handled as safely as possible.

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