# How to integrate Interzoid MCP with Autogen

```json
{
  "title": "How to integrate Interzoid MCP with Autogen",
  "toolkit": "Interzoid",
  "toolkit_slug": "interzoid",
  "framework": "AutoGen",
  "framework_slug": "autogen",
  "url": "https://composio.dev/toolkits/interzoid/framework/autogen",
  "markdown_url": "https://composio.dev/toolkits/interzoid/framework/autogen.md",
  "updated_at": "2026-05-12T10:16:08.678Z"
}
```

## Introduction

This guide walks you through connecting Interzoid to AutoGen using the Composio tool router. By the end, you'll have a working Interzoid agent that can match duplicate customer records by name, verify email addresses in a contact list, enrich company data with industry details through natural language commands.
This guide will help you understand how to give your AutoGen agent real control over a Interzoid account through Composio's Interzoid MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Interzoid with

- [OpenAI Agents SDK](https://composio.dev/toolkits/interzoid/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/interzoid/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/interzoid/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/interzoid/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/interzoid/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/interzoid/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/interzoid/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/interzoid/framework/cli)
- [Google ADK](https://composio.dev/toolkits/interzoid/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/interzoid/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/interzoid/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/interzoid/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/interzoid/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/interzoid/framework/crew-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 Interzoid
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call Interzoid tools
- Run a live chat loop where you ask the agent to perform Interzoid 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 Interzoid MCP server, and what's possible with it?

The Interzoid MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Interzoid account. It provides structured and secure access to Interzoid's powerful data quality APIs, so your agent can perform actions like matching records, verifying data, enriching information, and analyzing datasets on your behalf.
- Data matching and deduplication: Let your agent detect and merge duplicate records across datasets using fuzzy and advanced matching algorithms.
- Real-time data verification: Have the agent verify email addresses, phone numbers, and other key data points to ensure accuracy and reliability.
- Data enrichment and augmentation: Automatically enhance your records with additional company, contact, or geographic information pulled from Interzoid's enrichment APIs.
- Similarity scoring and analysis: Enable your agent to compare names, addresses, or other fields for similarity, helping with record linkage or fraud detection.
- Automated quality checks: Easily set up workflows where your agent scans new or existing data for quality issues and suggests corrections or improvements.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `INTERZOID_ADDRESS_PARSE` | Parse Address | Tool to parse a free-form address into structured components. Use when you need to extract street, city, state, etc. from unstructured address strings. |
| `INTERZOID_EMAIL_TRUST_SCORE` | Interzoid Email Trust Score | Tool to return a trust score for an email address. Use when you need to assess the quality and legitimacy of an email address. Call after acquiring the target email. |
| `INTERZOID_GET_ADDRESS_MATCH_ADVANCED` | Get Address Match Advanced | Tool to generate a similarity key for a US street address. Use when performing fuzzy deduplication of addresses across datasets. |
| `INTERZOID_GET_AREA_CODE` | Get Area Code Information | Tool to retrieve telephone area code information including primary city and geographic locale. Use when you need to get details about a specific area code. |
| `INTERZOID_GET_AREA_CODE_FROM_NUMBER` | Get Area Code From Number | Tool to get area code information from a telephone number. Use when you need to identify the geographic location or area code details for a given phone number. |
| `INTERZOID_GET_BUSINESS_INFO` | Get Business Info | Tool to retrieve comprehensive company profiles and business intelligence. Use when you need detailed company information by name, domain, or email. |
| `INTERZOID_GET_COMPANY_MATCH_ADVANCED` | Get Company Match Advanced | Tool to generate a fuzzy-matching key for an organization name. Use when normalizing and deduplicating company names after extraction. |
| `INTERZOID_GET_COUNTRY_INFO` | Get Country Info | Tool to standardize a country name and return metadata like ISO codes, currency, TLD, and calling code. Use when you need detailed country information based on a country name or code. |
| `INTERZOID_GET_CURRENCY_RATE` | Get Currency Rate | Tool to retrieve live USD exchange rate for a currency symbol. Use when you need current market rate for a three-letter ISO 4217 currency. |
| `INTERZOID_GET_CUSTOM_DATA` | Get Custom Data | Tool to retrieve custom enriched data based on a topic and lookup value. Use after specifying the desired output fields. |
| `INTERZOID_GET_EMAIL_INFO` | Get Email Info | Tool to validate an email and return enrichment/demographics. Use when you need in-depth email analysis after confirming the email address. |
| `INTERZOID_GET_ENTITY_TYPE` | Get Entity Type | Tool to classify a text string into an entity type. Use when you need to identify if input refers to a Location, Organization, or Individual. |
| `INTERZOID_GET_EXECUTIVE_PROFILE` | Get Executive Profile | Tool to retrieve executive profile details based on company and title keywords. Use when you need executive information such as LinkedIn and biography links. |
| `INTERZOID_GET_FULL_NAME_MATCH` | Get Full Name Match | Tool to generate a similarity key for a full name. Use when performing fuzzy matching or deduplication of individual names. |
| `INTERZOID_GET_FULL_NAME_MATCH_SCORE` | Get Full Name Match Score | Tool to return a similarity score between two full names. Use when determining if two person names likely refer to the same individual. |
| `INTERZOID_GET_GLOBAL_ADDRESS_MATCH` | Get Global Address Match | Tool to generate a similarity key for a global address. Use when performing fuzzy matching and deduplication of international addresses. |
| `INTERZOID_GET_GLOBAL_PAGE_LOAD_PERFORMANCE` | Get Global Page Load Performance | Tool to measure page/API load time from a specified global origin. Use when benchmarking response times across geographic locations. |
| `INTERZOID_GET_GLOBAL_WEATHER` | Get Global Weather | Tool to return current weather conditions for a global location. Use when you need up-to-the-minute weather details for any city worldwide. |
| `INTERZOID_GET_IP_PROFILE` | Get IP Profile | Tool to retrieve IP intelligence including ASN, organization, geolocation, and reputation. Use when profiling an IP address for threat analysis. |
| `INTERZOID_GET_LICENSE` | Get API License Key | Tool to retrieve the configured Interzoid API license key. Use when you need to inspect which API key is active in the current connection. |
| `INTERZOID_GET_NAME_ORIGIN` | Get Name Origin | Tool to infer the likely country or region of origin from a personal name. Use after obtaining a name to guess its origin. |
| `INTERZOID_GET_ORG_MATCH_SCORE` | Get Org Match Score | Tool to return a 1–99 match score between two organization names. Use after gathering both names to evaluate organization similarity. |
| `INTERZOID_GET_ORG_STANDARD` | Get Org Standard | Tool to standardize an organization name to a canonical English form. Use when you need consistent company naming for data normalization. |
| `INTERZOID_GET_PARENT_COMPANY_INFO` | Get Parent Company Info | Tool to retrieve ultimate parent company information. Use when you have a company name or domain and need its ownership details. |
| `INTERZOID_GET_PHONE_PROFILE` | Get Phone Number Profile | Tool to retrieve phone number intelligence including validation, normalization, carrier, and risk assessment. Use when you need to enrich and validate a phone number after capture. |
| `INTERZOID_GET_PRODUCT_MATCH` | Get Product Match | Tool to generate a similarity key for a product name. Use when normalizing and fuzzy-matching names across catalogs. |
| `INTERZOID_GET_REMAINING_CREDITS` | Get Remaining API Credits | Tool to retrieve remaining Interzoid API credits. Use when you need to check your credit balance after usage. |
| `INTERZOID_GET_WEATHER_ZIPCODE` | Get Weather by ZIP Code | Tool to get current weather conditions for a US ZIP code. Use when you need real-time weather information for a specific area after confirming the ZIP code is valid. |
| `INTERZOID_IDENTIFY_LANGUAGE` | Identify Language | Tool to detect the language of a text string. Use when you need to identify the language of arbitrary text. Call after obtaining the text input. |
| `INTERZOID_TRANSLATE_TO_ANY` | Translate any text (auto-detect language) | Tool to auto-detect the input language and translate given text to the specified target language. Use when you need quick translations without specifying the source language. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Interzoid MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Interzoid. Instead of manually wiring Interzoid APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

You will need:
- A Composio API key
- An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
- A Interzoid account you can connect to Composio
- Some basic familiarity with Autogen and Python async

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

Install Composio, Autogen extensions, and dotenv.
What's happening:
- composio connects your agent to Interzoid via MCP
- autogen-agentchat provides the AssistantAgent class
- autogen-ext-openai provides the OpenAI model client
- autogen-ext-tools provides MCP workbench support
```bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools
```

### 3. Set up environment variables

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 Interzoid connections to use
```bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com
```

### 4. Import dependencies and create Tool Router session

What's happening:
- load_dotenv() reads your .env file
- Composio(api_key=...) initializes the SDK
- create(...) creates a Tool Router session that exposes Interzoid tools
- session.mcp.url is the MCP endpoint that Autogen will connect to
```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 Interzoid session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["interzoid"]
    )
    url = session.mcp.url
```

### 5. Configure MCP parameters for Autogen

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
```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")}
)
```

### 6. Create the model client and agent

What's happening:
- OpenAIChatCompletionClient wraps the OpenAI model for Autogen
- McpWorkbench connects the agent to the MCP tools
- AssistantAgent is configured with the Interzoid tools from the workbench
```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 Interzoid assistant agent with MCP tools
    agent = AssistantAgent(
        name="interzoid_assistant",
        description="An AI assistant that helps with Interzoid operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )
```

### 7. Run the interactive chat loop

What's happening:
- The script prompts you in a loop with You:
- Autogen passes your input to the model, which decides which Interzoid 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
```python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Interzoid 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")
```

## Complete Code

```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 Interzoid session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["interzoid"]
    )
    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 Interzoid assistant agent with MCP tools
        agent = AssistantAgent(
            name="interzoid_assistant",
            description="An AI assistant that helps with Interzoid 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 Interzoid 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 Interzoid 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 Interzoid, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

## How to build Interzoid MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/interzoid/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/interzoid/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/interzoid/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/interzoid/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/interzoid/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/interzoid/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/interzoid/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/interzoid/framework/cli)
- [Google ADK](https://composio.dev/toolkits/interzoid/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/interzoid/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/interzoid/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/interzoid/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/interzoid/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/interzoid/framework/crew-ai)

## Related Toolkits

- [Firecrawl](https://composio.dev/toolkits/firecrawl) - Firecrawl automates large-scale web crawling and data extraction. It helps organizations efficiently gather, index, and analyze content from online sources.
- [Tavily](https://composio.dev/toolkits/tavily) - Tavily offers powerful search and data retrieval from documents, databases, and the web. It helps teams locate and filter information instantly, saving hours on research.
- [Exa](https://composio.dev/toolkits/exa) - Exa is a data extraction and search platform for gathering and analyzing information from websites, APIs, or databases. It helps teams quickly surface insights and automate data-driven workflows.
- [Serpapi](https://composio.dev/toolkits/serpapi) - SerpApi is a real-time API for structured search engine results. It lets you automate SERP data collection, parsing, and analysis for SEO and research.
- [Peopledatalabs](https://composio.dev/toolkits/peopledatalabs) - Peopledatalabs delivers B2B data enrichment and identity resolution APIs. Supercharge your apps with accurate, up-to-date business and contact data.
- [Snowflake](https://composio.dev/toolkits/snowflake) - Snowflake is a cloud data warehouse built for elastic scaling, secure data sharing, and fast SQL analytics across major clouds.
- [Posthog](https://composio.dev/toolkits/posthog) - PostHog is an open-source analytics platform for tracking user interactions and product metrics. It helps teams refine features, analyze funnels, and reduce churn with actionable insights.
- [Amplitude](https://composio.dev/toolkits/amplitude) - Amplitude is a digital analytics platform for product and behavioral data insights. It helps teams analyze user journeys and make data-driven decisions quickly.
- [Bright Data MCP](https://composio.dev/toolkits/brightdata_mcp) - Bright Data MCP is an AI-powered web scraping and data collection platform. Instantly access public web data in real time with advanced scraping tools.
- [Browseai](https://composio.dev/toolkits/browseai) - Browseai is a web automation and data extraction platform that turns any website into an API. It's perfect for monitoring websites and retrieving structured data without manual scraping.
- [ClickHouse](https://composio.dev/toolkits/clickhouse) - ClickHouse is an open-source, column-oriented database for real-time analytics and big data processing using SQL. Its lightning-fast query performance makes it ideal for handling large datasets and delivering instant insights.
- [Coinmarketcal](https://composio.dev/toolkits/coinmarketcal) - CoinMarketCal is a community-powered crypto calendar for upcoming events, announcements, and releases. It helps traders track market-moving developments and stay ahead in the crypto space.
- [Control d](https://composio.dev/toolkits/control_d) - Control d is a customizable DNS filtering and traffic redirection platform. It helps you manage internet access, enforce policies, and monitor usage across devices and networks.
- [Databox](https://composio.dev/toolkits/databox) - Databox is a business analytics platform that connects your data from any tool and device. It helps you track KPIs, build dashboards, and discover actionable insights.
- [Databricks](https://composio.dev/toolkits/databricks) - Databricks is a unified analytics platform for big data and AI on the lakehouse architecture. It empowers data teams to collaborate, analyze, and build scalable solutions efficiently.
- [Datagma](https://composio.dev/toolkits/datagma) - Datagma delivers data intelligence and analytics for business growth and market discovery. Get actionable market insights and track competitors to inform your strategy.
- [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment.
- [Dovetail](https://composio.dev/toolkits/dovetail) - Dovetail is a research analysis platform for transcript review and insight generation. It helps teams code interviews, analyze feedback, and create actionable research summaries.
- [Dub](https://composio.dev/toolkits/dub) - Dub is a short link management platform with analytics and API access. Use it to easily create, manage, and track branded short links for your business.
- [Elasticsearch](https://composio.dev/toolkits/elasticsearch) - Elasticsearch is a distributed, RESTful search and analytics engine for all types of data. It delivers fast, scalable search and powerful analytics across massive datasets.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Interzoid MCP?

With a standalone Interzoid MCP server, the agents and LLMs can only access a fixed set of Interzoid tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Interzoid 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 Interzoid tools.

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

Yes, absolutely. You can configure which Interzoid 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 Interzoid data and credentials are handled as safely as possible.

---
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