How to integrate TiDB Cloud MCP with Pydantic AI

This guide walks you through connecting TiDB Cloud to Pydantic AI using the Composio tool router. By the end, you'll have a working TiDB Cloud agent that can list your clusters and branches, review audit logs, check your monthly bill, and list organization members through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a TiDB Cloud account through Composio's TiDB Cloud MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Introduction

This guide walks you through connecting TiDB Cloud to Pydantic AI using the Composio tool router. By the end, you'll have a working TiDB Cloud agent that can list your clusters and branches, review audit logs, check your monthly bill, and list organization members through natural language commands.

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

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

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

The TiDB Cloud MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your TiDB Cloud account. It provides structured and secure access to your cloud database resources, billing, audit activity, organization members, and Data Service applications, so your agent can review clusters, inspect monthly bills, search audit logs, track imports, and monitor applications on your behalf.

  • Cluster and region visibility: Have your agent list Starter, Essential, or Dedicated clusters, retrieve cluster details, and check available deployment regions.
  • Billing and audit reviews: Instruct your agent to retrieve monthly organization bills and search audit activity by time range, event type, or keyword.
  • Branches and import tracking: Let the agent list database branches and review import tasks, including their status, progress, source, timing, and errors.
  • Data Service monitoring: Direct your agent to list Data Service applications in a project and check their deployments and current deployment status.
  • Organization member oversight: Have your agent review organization members and narrow the results by identity, assignment, role, or status.

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

Get Cluster

Get details for one Starter/Essential instance or Dedicated cluster by ID.

Get Monthly Bill

Return the TiDB Cloud organization bill for one calendar month.

List Audit Logs

Search TiDB Cloud organization audit logs by time range, event type, or keyword and return one page of results.

List Branches

List database branches for a TiDB Cloud Starter or Essential instance.

List Clusters

List TiDB Cloud Starter/Essential instances or Dedicated clusters, with product-specific filters.

List Data App Deployments

List one page of deployments and deployment status for a TiDB Cloud Data Service application, plus a continuation cursor.

List Data Apps

List TiDB Cloud Data Service applications in a project, returning one page and a continuation cursor.

List Import Tasks

List one page of import tasks for a TiDB Cloud Starter/Essential instance or Dedicated cluster, including status, progress, source, timestamps, errors, and a continuation cursor.

List Organization Members

List one page of TiDB Cloud organization members with optional identity, assignment, role, and status filters, plus a continuation cursor.

List Regions

List regions available for Starter/Essential or Dedicated clusters, optionally filtering Dedicated regions.

FRAMEWORKS

How to build TiDB Cloud MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use TiDB Cloud MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use TiDB Cloud MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use TiDB Cloud MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use TiDB Cloud MCP with Claude Cowork

Codex logo

Codex

Use TiDB Cloud MCP with Codex

OpenClaw logo

OpenClaw

Use TiDB Cloud MCP with OpenClaw

Hermes logo

Hermes

Use TiDB Cloud MCP with Hermes

CLI logo

CLI

Use TiDB Cloud MCP with CLI

Google ADK logo

Google ADK

Use TiDB Cloud MCP with Google ADK

LangChain logo

LangChain

Use TiDB Cloud MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use TiDB Cloud MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use TiDB Cloud MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use TiDB Cloud MCP with LlamaIndex

CrewAI logo

CrewAI

Use TiDB Cloud MCP with CrewAI

FAQ

Frequently asked questions

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

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

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