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How to integrate Grafbase MCP with Pydantic AI

Connect Pydantic AI to Grafbase MCP. Retrieve the latest audit log entry, delete a specific api key by id, and more using natural language, with authentication handled for you.

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Grafbase is a platform for building and scaling GraphQL APIs with edge caching and unified data access. It's designed to help you deliver fast, secure, and seamless APIs—all in one place.

28 Tools

Introduction

This guide walks you through connecting Grafbase to Pydantic AI using the Composio tool router. By the end, you'll have a working Grafbase agent that can fetch federated and subgraph schemas, review schema checks, enable and disable MCP servers, browse audit logs, and manage API keys through natural language commands.

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

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

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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 Grafbase
  • 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 Grafbase 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 Grafbase MCP server, and what's possible with it?

The Grafbase MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, and more directly to your Grafbase account. It provides structured and secure access to your GraphQL API management, so your agent can perform actions like enabling or disabling MCP, managing API keys, retrieving schemas, and working with audit logs on your behalf.

  • Enable or disable MCP server: Instantly activate or turn off the Model Context Protocol for your Grafbase project, all by agent command.
  • API key management: Let your agent securely delete existing API keys to control and rotate access as needed.
  • Schema and federation management: Retrieve federated graph schemas or remove unwanted schemas for streamlined development workflows.
  • Audit log retrieval: Fetch specific audit log entries, giving your agent the power to surface key changes or events in your Grafbase environment.
  • Extension and server configuration cleanup: Delete extension configurations or obsolete MCP server setups to keep your backend lean and secure.

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

Add Zitadel Redirect URI

Request addition of a Zitadel OAuth redirect in Grafbase using the authenticated context.

Assign Team Role

Tool to assign a role to a team member in Grafbase.

Delete Grafbase API Key

Delete a Grafbase API key (access token) by ID.

Delete Grafbase Audit Log

Tool to delete a specific Grafbase audit log entry.

Delete Extension

Attempt to delete a Grafbase extension configuration by its unique ID through the project API.

Delete MCP Server

Attempt to delete a Grafbase MCP server configuration by its unique ID through the project API.

Delete Grafbase Subgraph

Tool to delete a subgraph from a Grafbase federated graph.

Delete Schema Check

Query a Grafbase schema check by ID and return information about the check or an API error.

Delete Grafbase Team

Tool to delete a team from the Grafbase organization.

Disable MCP Server

Attempt to disable the Model Context Protocol (MCP) server for a Grafbase project through its API.

Enable Grafbase MCP Server

Attempt to enable MCP on a Grafbase gateway via its API, returning manual configuration guidance if the endpoint is unsupported or unreachable.

Get Grafbase Audit Log

Search accessible Grafbase organization members by user ID, name, email, or role, optionally scoped to an organization.

Get Extension by Name

Tool to retrieve a Grafbase extension by its name.

Get Extension Version By Name And Version

Tool to retrieve details of a specific Grafbase extension version by name and version.

Get Federated Schema

Retrieves the composed federated graph schema from Grafbase in SDL format.

Get Grafbase Invitation

Retrieve details of a specific Grafbase invitation by ID, including its status, email address, and creation date.

Get Notifications Inbox Messages

Tool to retrieve notifications inbox messages for the authenticated Grafbase user.

Get Grafbase Schema Check

Retrieve a Grafbase schema check by ID within an account and graph, returning its error count, subgraph name and available Git commit information.

Get Subgraph Schema

Retrieve the GraphQL SDL schema for a subgraph by name.

List API Keys

List all API keys (access tokens) for the authenticated Grafbase user.

List Grafbase Audit Logs

List Grafbase organization member-join activity derived from organization membership data, with optional organization filtering.

List Extensions

List extensions returned by available Grafbase project REST endpoints.

List MCP Servers

Check a Grafbase gateway's presumed /mcp endpoint and provide configuration guidance.

List Grafbase Schema Checks

List schema checks for a Grafbase graph.

List Grafbase Schemas

Tool to list all schemas in the Grafbase schema registry.

List Grafbase Subgraphs

List published subgraphs and their endpoint URLs across Grafbase organizations, optionally filtering by branch name.

Mark Notifications as Read

Tool to mark Grafbase notifications as read.

Remove Graph Owner

Tool to remove an owner from a Grafbase graph.

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LlamaIndex

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CrewAI

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AutoGen logo

AutoGen

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FAQ

Frequently asked questions

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

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

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