How to integrate Dadata ru MCP with Pydantic AI

This guide walks you through connecting Dadata ru to Pydantic AI 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 through natural language commands. This guide will help you understand how to give your Pydantic AI 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.

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Dadata ru is a data validation and enrichment API for Russian addresses, companies, and personal data. It helps automate data entry, reduce errors, and standardize records across your workflows.

63 Tools

Introduction

This guide walks you through connecting Dadata ru to Pydantic AI 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 through natural language commands.

This guide will help you understand how to give your Pydantic AI 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.

Also integrate Dadata ru with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

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 Dadata ru
  • 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 Dadata ru 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 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.

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 step09 STEPS
1

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
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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Dadata ru
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

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
5

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 Dadata ru
  • MCPServerStreamableHTTP connects to the Dadata ru MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

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 Dadata ru
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["dadata_ru"],
    )
    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 Dadata ru 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
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
dadata_ru_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[dadata_ru_mcp],
    instructions=(
        "You are a Dadata ru assistant. Use Dadata ru tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Dadata ru endpoint
  • The agent uses GPT-5 to interpret user commands and perform Dadata ru operations
  • The instructions field defines the agent's role and behavior
8

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 Dadata ru.\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
  • Dadata ru API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

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 Dadata ru 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 Dadata ru
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["dadata_ru"],
    )
    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
    dadata_ru_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[dadata_ru_mcp],
        instructions=(
            "You are a Dadata ru assistant. Use Dadata ru 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 Dadata ru.\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 Dadata ru through Composio's Tool Router. With this setup, your agent can perform real Dadata ru 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 + Dadata ru for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

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

Clean Address

Clean and standardize a Russian postal address.

Clean Birthdate

Standardize and validate birthdate strings.

Clean Email

Standardize and validate an email address.

Clean Name (FIO)

Tool to standardize and parse full names (FIO), detect gender, and return grammatical cases.

Clean Passport

Tool to validate a Russian passport number against the official registry.

Clean Phone

Tool to standardize and validate phone numbers.

Clean Composite Record

Tool to standardize composite records with multiple contact data fields in a single request.

Clean Vehicle

Standardize and recognize vehicle make/model from free-form text input.

Find Address

Retrieve full Russian address details by FIAS ID, KLADR code, or cadastral number.

Find Bank

Tool to find bank by BIC, SWIFT, INN, or registration number.

Find Car Brand

Find car brand details by identifier.

Find Company By Email

Find companies by corporate email address domain.

Find Country

Tool to find country details by ISO or numeric code.

Find Court by ID

Find court by ID or code.

Find Currency

Tool to find currency details by ISO 4217 code.

Find Delivery City IDs

Retrieves delivery service city identifiers (CDEK, Boxberry, DPD) for a given Russian city by KLADR code or FIAS ID.

Find Address by FIAS ID

Find address by FIAS ID from the Federal Information Address System (FIAS/GAR).

Find FMS Unit

Look up Russian passport issuing authority (FMS unit) by subdivision code.

Find FNS Unit by Code

Find Russian tax inspection (FNS unit) by exact code or INN.

Find FTS Unit

Find a Russian Federal Customs Service (FTS) unit by its 8-digit code.

Find Medical Position By ID

Tool to find medical position by ID code.

Find MKTU

Look up MKTU (International Classification of Goods and Services/Nice Classification) items by their numeric code.

Find OKPD2 by ID

Look up OKPD2 (Russian Classification of Products by Economic Activity) entries by their exact code.

Find OKPDTR Position

Find job position by OKPDTR code.

Find OKPDTR Profession

Tool to find profession details by OKPDTR code.

Find Territory by OKTMO

Find Russian municipal territory by OKTMO code.

Find OKVED2

Look up OKVED2 (Russian Classification of Economic Activities) entries by their exact code.

Find Company or Entrepreneur

Find company or individual entrepreneur details by INN or OGRN from the Russian Federal Tax Service registry.

Find Belarus Party by UNP

Tool to find a Belarusian company or entrepreneur by UNP.

Find Kazakhstan Company by BIN

Look up Kazakhstan company or entrepreneur details by BIN (Business Identification Number).

Find Postal Office

Find Russian postal office details by postal code (index).

Find Postal Unit By ID

Find postal unit by postal code.

Geolocate Address

Tool to find nearest addresses by geographic coordinates.

Geolocate Postal Unit

Tool to find nearest postal units by geographic coordinates.

Get Profile Balance

Tool to retrieve current DaData account balance.

Get Profile Statistics

Tool to get daily aggregated usage statistics per DaData API service.

Get Reference Versions

Tool to retrieve the last update dates for DaData reference datasets (FIAS, EGRUL, banks, etc.

IP Locate Address

Geolocate a Russian IP address to determine its city/region.

Suggest Address

Tool to autocomplete and suggest addresses.

Suggest Bank

Tool to autocomplete and suggest banks by partial details.

Suggest Car Brand

Tool to suggest car brands.

Suggest Country

Tool to suggest countries based on user input.

Suggest Court

Tool to suggest Russian courts by name or location.

Suggest Currency

Tool to suggest currencies by ISO 4217 code or name.

Suggest Email

Tool to autocomplete and suggest email addresses.

Suggest FIAS Address

Tool to suggest addresses from FIAS/GAR database.

Suggest FMS Unit

Tool to autocomplete and suggest passport issuing authorities.

Suggest FNS Unit

Tool to suggest Russian tax inspection units by partial name or code.

Suggest FTS Unit

Tool to autocomplete and suggest Russian customs (FTS) units.

Suggest Medical Position

Tool to autocomplete and suggest medical positions and specialties.

Suggest Metro

Tool to suggest metro stations.

Suggest MKTU

Autocomplete and search for MKTU (Nice Classification) codes used for trademark registration.

Suggest Name

Tool to autocomplete and suggest full names (FIO).

Suggest OKPD2

Tool to autocomplete and suggest Russian product classification codes (OKPD2).

Suggest OKPDTR Position

Tool to autocomplete and suggest Russian job positions from OKPDTR classifier.

Suggest OKPDTR Profession

Tool to autocomplete and suggest professions from OKPDTR classifier.

Suggest OKTMO

Suggest Russian municipal territory codes (OKTMO) by code prefix or partial name.

Suggest OKVED2

Tool to suggest OKVED2 codes by text query.

Suggest Party

Tool to autocomplete and suggest Russian companies or entrepreneurs.

Suggest Belarus Party

Tool to autocomplete and suggest Belarusian companies or entrepreneurs.

Suggest Kazakhstan Company

Tool to autocomplete and suggest Kazakhstan companies or entrepreneurs.

Suggest Postal Office

Suggests Russian Post offices by postal code or address.

Suggest Postal Unit

Suggests Russian Post offices (Почта России) by postal code or address.

FRAMEWORKS

How to build Dadata ru MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Dadata ru MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Dadata ru MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Dadata ru MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Dadata ru MCP with Claude Cowork

Codex logo

Codex

Use Dadata ru MCP with Codex

OpenClaw logo

OpenClaw

Use Dadata ru MCP with OpenClaw

Hermes logo

Hermes

Use Dadata ru MCP with Hermes

CLI logo

CLI

Use Dadata ru MCP with CLI

Google ADK logo

Google ADK

Use Dadata ru MCP with Google ADK

LangChain logo

LangChain

Use Dadata ru MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Dadata ru MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Dadata ru MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Dadata ru MCP with LlamaIndex

CrewAI logo

CrewAI

Use Dadata ru MCP with CrewAI

FAQ

Frequently asked questions

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.

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 Dadata ru tools.

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.

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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Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

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Co-founder, Opennote

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As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

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Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

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