How to integrate Dadata ru MCP with Autogen

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Introduction

This guide walks you through connecting Dadata ru to AutoGen using the Composio tool router. By the end, you'll have a working Dadata ru agent that can clean and standardize this russian address, validate and parse a user's full name, check if this passport number is valid, get full bank details from a bic code through natural language commands.

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

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

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

The Dadata ru MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Dadata ru account. It provides structured and secure access to DaData’s powerful data validation and enrichment APIs, so your agent can perform actions like standardizing addresses, cleaning contact details, parsing names, and retrieving company or bank information on your behalf.

  • Accurate address standardization and parsing: Instantly clean and structure messy Russian addresses or retrieve address details using identifiers like cadastral numbers or FIAS IDs.
  • Email, phone, and passport validation: Let your agent validate and clean raw email addresses, phone numbers, or Russian passport numbers to ensure your data is correct and safe to use.
  • Full name parsing and gender detection: Automatically break down full names (FIO), identify gender, and get grammatical declensions to power advanced personalization or document processing.
  • Vehicle and car brand data enrichment: Extract structured vehicle details and fetch comprehensive car brand information by code for registration or verification workflows.
  • Bank information retrieval: Quickly find complete bank details by BIC, SWIFT, INN, or registration numbers, streamlining financial processes and verifications.

Supported Tools & Triggers

Tools
Clean AddressTool to clean and standardize russian postal addresses.
Clean BirthdateTool to standardize and validate birthdate strings.
Clean EmailTool to standardize and validate email addresses.
Clean Name (FIO)Tool to standardize and parse full names (fio), detect gender, and return grammatical cases.
Clean PassportTool to validate a russian passport number against the official registry.
Clean PhoneTool to standardize and validate phone numbers.
Clean VehicleTool to standardize and parse vehicle data fields.
Find AddressTool to find address by identifier.
Find BankTool to find bank by bic, swift, inn, or registration number.
Find Car BrandTool to find car brand by its identifier.
Find CountryTool to find country details by iso or numeric code.
Find CurrencyTool to find currency details by iso 4217 code.
Find Delivery City IDsTool to get delivery service city ids by kladr code.
Find FMS UnitTool to find passport authority (fms unit) by code.
Find FTS UnitTool to find customs (fts) office by code.
Find MKTUTool to find mktu classification details by code.
Find OKVED2Tool to find okved2 classifier entries by code.
Find Company or EntrepreneurTool to find company or individual entrepreneur details by inn, ogrn, or kpp.
Find Belarus Party by UNPTool to find a belarusian company or entrepreneur by unp.
Find Kazakhstan Company by BINTool to find kazakhstan company or entrepreneur details by bin or name.
Geolocate AddressTool to find nearest addresses by geographic coordinates.
Get Profile BalanceTool to retrieve current dadata account balance.
Get Profile StatisticsTool to get daily aggregated usage statistics per dadata api service.
Get Reference VersionsTool to retrieve the last update dates for dadata reference datasets (fias, egrul, banks, etc.
IP Locate AddressTool to determine russian address by ip.
Suggest AddressTool to autocomplete and suggest addresses.
Suggest BankTool to autocomplete and suggest banks by partial details.
Suggest Car BrandTool to suggest car brands.
Suggest CourtTool to suggest russian courts by name or location.
Suggest CurrencyTool to suggest currencies by iso 4217 code or name.
Suggest EmailTool to autocomplete and suggest email addresses.
Suggest FMS UnitTool to autocomplete and suggest passport issuing authorities.
Suggest FNS UnitTool to suggest russian tax inspection units by partial name or code.
Suggest FTS UnitTool to autocomplete and suggest russian customs (fts) units.
Suggest MetroTool to suggest metro stations.
Suggest MKTUTool to suggest mktu entries.
Suggest NameTool to autocomplete and suggest full names (fio).
Suggest OKPD2Tool to autocomplete and suggest russian product classification codes (okpd2).
Suggest OKTMOTool to suggest russian municipal territory codes (oktmo).
Suggest OKVED2Tool to suggest okved2 codes by text query.
Suggest PartyTool to autocomplete and suggest russian companies or entrepreneurs.
Suggest Postal UnitTool to suggest russian postal units by index or coordinates.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Dadata ru 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 Dadata ru 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 Dadata ru 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 Dadata ru session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["dadata_ru"]
    )
    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 Dadata ru 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 Dadata ru assistant agent with MCP tools
    agent = AssistantAgent(
        name="dadata_ru_assistant",
        description="An AI assistant that helps with Dadata ru 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 Dadata ru 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 Dadata ru 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 Dadata ru 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 Dadata ru and AutoGen:

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

How to build Dadata ru MCP Agent with another framework

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OpenAI Agents SDK

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Claude Agent SDK

Claude Agent SDK

Use Dadata ru MCP with Claude Agent SDK

Google ADK

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Use Dadata ru MCP with Google ADK

LangChain

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Use Dadata ru MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Dadata ru MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Dadata ru MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Dadata ru MCP with LlamaIndex

CrewAI

CrewAI

Use Dadata ru MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Dadata ru MCP?

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

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

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

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