How to integrate Supermemory MCP with Pydantic AI

This guide walks you through connecting Supermemory to Pydantic AI using the Composio tool router. By the end, you'll have a working Supermemory agent that can store your documents, search your memories, recall saved context, and update documents through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Supermemory account through Composio's Supermemory MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Supermemory is a memory and context API for ingesting, organizing, searching, and recalling information. Use it to give apps durable, searchable context without rebuilding memory infrastructure.

11 Tools

Introduction

This guide walks you through connecting Supermemory to Pydantic AI using the Composio tool router. By the end, you'll have a working Supermemory agent that can store your documents, search your memories, recall saved context, and update documents through natural language commands.

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

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

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

The Supermemory MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Supermemory account. It provides structured and secure access to your documents, memories, learned profiles, and account usage, so your agent can ingest information, organize documents, search context, recall memories, and review usage on your behalf.

  • Document ingestion and organization: Have your agent add text, public web content, or document collections, then organize them with containers, metadata, and file paths.
  • Memory and context search: Instruct your agent to search memories, document content, or both by meaning, with optional container and metadata filters.
  • Document review and management: Let the agent list documents, inspect their content and processing status, review extracted chunks, update stored information, or delete documents.
  • Memory and profile recall: Direct your agent to list extracted memories or retrieve learned profiles for a container, with matching search results when needed.
  • Account usage checks: Have your agent review your Supermemory plan, credit balance, overall usage, and reset date.

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

Add Document

Ingest text or a public URL as a Supermemory document and return its document ID and initial processing status.

Add Documents

Add 1 to 600 documents in one request, with explicit per-document metadata and processing options.

Delete Document

Permanently delete one document by ID.

Get Account Status

Return the connected Supermemory organization's plan, credit balance, high-level usage, and reset date.

Get Document

Get one document's content, metadata, source details, and processing status by document ID.

Get Document Chunks

Return the ordered extracted chunks for one processed document.

Get Profile

Retrieve the static, dynamic, or bucketed profile learned for one container tag, optionally with matching search results.

List Documents

List documents, optionally filtered by containers, metadata, or filepath, one page at a time.

List Memories

List extracted memory entries for one or more container tags, one page at a time.

Search Memory

Semantically search Supermemory memories, document chunks, or both, with optional container and metadata filters.

Update Document

Update the content, metadata, container, or processing configuration of one existing document.

FRAMEWORKS

How to build Supermemory MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Supermemory MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Supermemory MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Supermemory MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Supermemory MCP with Claude Cowork

Codex logo

Codex

Use Supermemory MCP with Codex

OpenClaw logo

OpenClaw

Use Supermemory MCP with OpenClaw

Hermes logo

Hermes

Use Supermemory MCP with Hermes

CLI logo

CLI

Use Supermemory MCP with CLI

Google ADK logo

Google ADK

Use Supermemory MCP with Google ADK

LangChain logo

LangChain

Use Supermemory MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Supermemory MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Supermemory MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Supermemory MCP with LlamaIndex

CrewAI logo

CrewAI

Use Supermemory MCP with CrewAI

FAQ

Frequently asked questions

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

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

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