How to integrate Dadata ru MCP with CrewAI

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Introduction

This guide walks you through connecting Dadata ru to CrewAI 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 CrewAI 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 a Composio API key and configure your Dadata ru connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Dadata ru
  • Build a conversational loop where your agent can execute Dadata ru operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Dadata ru connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

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 crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Dadata ru via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env

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_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

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

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")
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Dadata ru MCP URL

Create a Composio Tool Router session for Dadata ru

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["dadata_ru"])

url = session.mcp.url
What's happening:
  • You create a Dadata ru only session through Composio
  • Composio returns an MCP HTTP URL that exposes Dadata ru tools

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's Happening:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

Here's the complete code to get you started with Dadata ru and CrewAI:

from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

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

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_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.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["dadata_ru"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Dadata ru through Composio's Tool Router. The agent can perform Dadata ru operations through natural language commands.

Next steps:

  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

How to build Dadata ru MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

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Claude Agent SDK

Claude Agent SDK

Use Dadata ru MCP with Claude Agent SDK

Google ADK

Google ADK

Use Dadata ru MCP with Google ADK

LangChain

LangChain

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

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 CrewAI?

Yes, you can. CrewAI 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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