How to integrate Backendless MCP with Pydantic AI

This guide walks you through connecting Backendless to Pydantic AI using the Composio tool router. By the end, you'll have a working Backendless agent that can list all files in the user uploads folder, create a new directory for project assets, retrieve users where status is active through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Backendless account through Composio's Backendless MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Backendless is a backend-as-a-service platform for mobile and web apps, offering database, file storage, user authentication, and APIs. It helps developers ship scalable applications faster without managing server infrastructure.

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Introduction

This guide walks you through connecting Backendless to Pydantic AI using the Composio tool router. By the end, you'll have a working Backendless agent that can list all files in the user uploads folder, create a new directory for project assets, retrieve users where status is active through natural language commands.

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

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

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

The Backendless MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Backendless account. It provides structured and secure access to your backend services, so your agent can perform actions like managing file storage, retrieving and updating database records, handling directories, and orchestrating server-side logic on your behalf.

  • Dynamic file and directory management: Allow your agent to create, copy, delete, and list files or folders in your Backendless storage, keeping your app data organized.
  • Database record retrieval and filtering: Empower the agent to fetch objects from specific tables with advanced filtering, sorting, and pagination for instant data access.
  • Automated backend task scheduling: Let the agent create or delete timers to run recurring or one-off server-side logic, enabling powerful backend automation.
  • Custom Hive resource management: Instruct your agent to create new Backendless Hive resources and retrieve full maps of stored values for scalable, flexible data handling.
  • Safe data cleanup: Make it easy for your agent to remove obsolete files, directories, or scheduled tasks, helping maintain a tidy and efficient backend environment.

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

Copy File

Tool to copy a file or directory within Backendless file storage.

Create Directory

Tool to create a new directory at the specified path.

Create Backendless Hive

Tool to create a new Hive.

Create Backendless Timer

Tool to create a new timer with schedule and code.

Delete Directory

Tool to delete a directory at the specified path in Backendless file storage.

Delete File

Deletes a file from Backendless file storage at the specified path.

Delete Backendless Timer

Deletes a Backendless timer by its unique name.

Directory Listing

Tool to retrieve a listing of files and directories at a given path.

General Object Retrieval

Tool to retrieve objects from a specified Backendless table with filtering, sorting, and pagination.

Get All Values

Tool to retrieve all values from a map in a specified Hive.

Get Counter Value

Tool to retrieve the current value of a Backendless counter.

Get File Count

Tool to get the count of files in a Backendless directory.

Get Key Items

Tool to retrieve values for a specified key in a list (all, single, or range).

Get Backendless Timer

Tool to retrieve information about a specific timer.

Map Put

Tool to set or update key-value pairs in a Hive map.

Move File

Tool to move a file or directory within Backendless file storage.

Publish Message

Tool to publish a message to a specified messaging channel.

Reset Counter

Tool to reset a Backendless counter back to zero.

Set Counter Value

Tool to set a Backendless counter to a specific value conditionally.

Update Backendless Timer

Tool to update schedule or code of an existing timer.

Delete User

Tool to delete a user by user ID.

Find User by ID

Tool to retrieve user information by ID.

Grant Permission to User

Tool to grant a permission to a user on a specific data object.

User Login

Tool to log in a registered user with identity and password.

User Logout

Tool to log out the currently authenticated user.

User Password Recovery

Tool to initiate password recovery for a user.

User Registration

Tool to register a new user with email and password.

Revoke Permission from User

Tool to revoke a permission from a specified user or role on a specific data object.

Update User

Tool to update properties of an existing Backendless user.

Validate User Token

Tool to validate a user session token.

FRAMEWORKS

How to build Backendless MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Backendless MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Backendless MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Backendless MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Backendless MCP with Claude Cowork

Codex logo

Codex

Use Backendless MCP with Codex

OpenClaw logo

OpenClaw

Use Backendless MCP with OpenClaw

Hermes logo

Hermes

Use Backendless MCP with Hermes

CLI logo

CLI

Use Backendless MCP with CLI

Google ADK logo

Google ADK

Use Backendless MCP with Google ADK

LangChain logo

LangChain

Use Backendless MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Backendless MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Backendless MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Backendless MCP with LlamaIndex

CrewAI logo

CrewAI

Use Backendless MCP with CrewAI

FAQ

Frequently asked questions

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

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

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