How to integrate Didit MCP with Pydantic AI

This guide walks you through connecting Didit to Pydantic AI using the Composio tool router. By the end, you'll have a working Didit agent that can review pending didit kyc verification sessions, check aml risk flags for users, create identity verification for new customer through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Didit account through Composio's Didit MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Didit is an identity verification and compliance API platform for KYC, KYB, AML, and fraud prevention. It helps teams onboard users faster while reducing risk and meeting compliance needs.

10 Tools

Introduction

This guide walks you through connecting Didit to Pydantic AI using the Composio tool router. By the end, you'll have a working Didit agent that can review pending didit kyc verification sessions, check aml risk flags for users, create identity verification for new customer through natural language commands.

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

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

Also integrate Didit 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 Didit
  • 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 Didit 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 Didit MCP server, and what's possible with it?

The Didit MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Didit account. It provides structured and secure access to identity verification, KYC, KYB, compliance workflows, and billing information, so your agent can create verification sessions, review decisions, inspect user and business profiles, check workflows, and monitor billing balance on your behalf.

  • Verification session creation: Have your agent create a hosted KYC or KYB verification session from a published workflow and provide the verification link to the applicant.
  • Verification review: Direct your agent to retrieve the latest decision and available feature reports for a verification session.
  • User and business oversight: Let the agent fetch individual KYC or KYB profiles, or list users and businesses with their statuses, verification summaries, and session activity.
  • Workflow planning: Instruct your agent to list configured verification workflows and review their publication status, included checks, configuration, and expected pricing.
  • Session and balance monitoring: Have your agent list and filter verification sessions, then check your prepaid credit balance and auto-refill settings before starting billable work.

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 Didit
  • 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 Didit
  • MCPServerStreamableHTTP connects to the Didit 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 Didit
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["didit"],
    )
    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 Didit 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
didit_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[didit_mcp],
    instructions=(
        "You are a Didit assistant. Use Didit tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Didit endpoint
  • The agent uses GPT-5 to interpret user commands and perform Didit 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 Didit.\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
  • Didit 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 Didit 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 Didit
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["didit"],
    )
    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
    didit_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[didit_mcp],
        instructions=(
            "You are a Didit assistant. Use Didit 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 Didit.\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 Didit through Composio's Tool Router. With this setup, your agent can perform real Didit 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 + Didit 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 Didit action and event your agent gets out of the box.

Create Verification Session

Create a hosted KYC or KYB verification session from a published workflow and return the URL to give the end user.

Get Billing Balance

Read the organization's prepaid Didit credit balance and auto-refill settings before starting billable verification work.

Get Business

Fetch one aggregated KYB business profile by its exact vendor_data identifier.

Get User

Fetch one aggregated KYC user profile by its exact vendor_data identifier.

Get Verification Decision

Retrieve the complete current KYC or KYB decision and all feature reports for one verification session.

Get Workflow

Fetch the full configuration and pricing of one workflow version.

List Businesses

List business profiles aggregated from KYB sessions, including status, session counts, registry identifiers, and verification summaries.

List Users

List user profiles aggregated from KYC sessions, including status, session counts, and feature summaries.

List Verification Sessions

List and filter KYC, KYB, or standalone verification sessions.

List Workflows

List configured verification workflow versions, their publication status, feature summary, and expected per-run pricing.

FRAMEWORKS

How to build Didit MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Didit MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Didit MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Didit MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Didit MCP with Claude Cowork

Codex logo

Codex

Use Didit MCP with Codex

OpenClaw logo

OpenClaw

Use Didit MCP with OpenClaw

Hermes logo

Hermes

Use Didit MCP with Hermes

CLI logo

CLI

Use Didit MCP with CLI

Google ADK logo

Google ADK

Use Didit MCP with Google ADK

LangChain logo

LangChain

Use Didit MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Didit MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Didit MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Didit MCP with LlamaIndex

CrewAI logo

CrewAI

Use Didit MCP with CrewAI

FAQ

Frequently asked questions

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

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

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