How to integrate Wit ai MCP with Pydantic AI

This guide walks you through connecting Wit ai to Pydantic AI using the Composio tool router. By the end, you'll have a working Wit ai agent that can analyze user message for intent and entities, list all custom traits in your wit app, get details of the 'bookflight' intent through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Wit ai account through Composio's Wit ai MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Wit.ai is a natural language processing platform that turns text or speech into structured data. It's perfect for building voice and chat interfaces that truly understand users.

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Introduction

This guide walks you through connecting Wit ai to Pydantic AI using the Composio tool router. By the end, you'll have a working Wit ai agent that can analyze user message for intent and entities, list all custom traits in your wit app, get details of the 'bookflight' intent through natural language commands.

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

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

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

The Wit ai MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Wit ai account. It provides structured and secure access to your NLP resources, so your agent can create and manage apps, analyze natural language, organize intents and traits, and update configurations on your behalf.

  • Instant natural language analysis: Let your agent extract intents, entities, and traits from any text message using Wit.ai’s advanced NLP engine.
  • Automated app management: Easily create, update, or delete Wit.ai apps, enabling rapid deployment and maintenance of your language models.
  • Intent and trait organization: Have your agent list, retrieve details, or update all defined intents and traits, keeping your language understanding models organized and up to date.
  • Full app metadata access: Fetch comprehensive app settings and metadata for better monitoring, debugging, or auditing of your NLP solutions.
  • Seamless entity and trait customization: Programmatically add or configure traits for tailored entity recognition and improved intent matching.

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

Add Entity Keyword

Tool to add a keyword with optional synonyms to a Wit.

Add Keyword Synonym

Tool to add a new synonym to a keyword in an entity.

Add Value to Trait

Tool to add a new value to an existing trait in Wit.

Create Wit.ai App

Tool to create a new app in Wit.

Create Wit.ai Entity

Tool to create a new entity in Wit.

Create Wit.ai Intent

Tool to create a new intent in Wit.

Create Wit.ai Trait

Tool to create a new trait in Wit.

Create Wit.ai Training Utterances

Tool to add training utterances (samples with annotations) to your Wit.

Delete App

Tool to delete a specific app from wit.

Delete Entity

Tool to permanently delete an entity by name.

Delete Entity Keyword

Tool to delete a keyword from a keywords entity in wit.

Delete Entity Role

Tool to delete a specific role from an entity in wit.

Delete Intent

Tool to permanently delete an intent by name.

Delete Keyword Synonym

Tool to delete a synonym from a keyword in an entity.

Delete Utterances

Tool to delete validated utterances (training samples) from your Wit.

Wit.ai Detect Language

Tool to detect the language of a given text input.

Export App Data

Tool to export Wit.

Get App Details

Tool to retrieve metadata and settings of a Wit.

Get Entity Details

Tool to retrieve details of a specific entity including keywords and roles.

Get Intent Details

Tool to retrieve details of a specific intent.

Get Intents

Tool to list all intents in a Wit.

Wit.ai Get Message

Tool to analyze a text message and extract its intent, entities, and traits.

Get Trait Details

Tool to retrieve details of a specific trait.

List Traits

Tool to list all traits in a Wit.

Get Voice Details

Tool to retrieve details for a specific text-to-speech voice.

List Wit.ai Apps

Tool to retrieve the list of all Wit.

List App Tags

Tool to retrieve all tag groups (versions) for a Wit.

List Entities

Tool to list all entities in a Wit.

List Utterances

Tool to retrieve training utterances (samples) from a Wit.

List Voices

Tool to retrieve all available text-to-speech voices grouped by locale.

Update Wit.ai App

Tool to update an existing Wit.

FRAMEWORKS

How to build Wit ai MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Wit ai MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Wit ai MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Wit ai MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Wit ai MCP with Claude Cowork

Codex logo

Codex

Use Wit ai MCP with Codex

OpenClaw logo

OpenClaw

Use Wit ai MCP with OpenClaw

Hermes logo

Hermes

Use Wit ai MCP with Hermes

CLI logo

CLI

Use Wit ai MCP with CLI

Google ADK logo

Google ADK

Use Wit ai MCP with Google ADK

LangChain logo

LangChain

Use Wit ai MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Wit ai MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Wit ai MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Wit ai MCP with LlamaIndex

CrewAI logo

CrewAI

Use Wit ai MCP with CrewAI

FAQ

Frequently asked questions

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

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

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