How to integrate Grafbase MCP with Autogen

This guide walks you through connecting Grafbase to AutoGen using the Composio tool router. By the end, you'll have a working Grafbase agent that can retrieve the latest audit log entry, delete a specific api key by id, get the current federated graph schema through natural language commands. This guide will help you understand how to give your AutoGen 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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Introduction

This guide walks you through connecting Grafbase to AutoGen using the Composio tool router. By the end, you'll have a working Grafbase agent that can retrieve the latest audit log entry, delete a specific api key by id, get the current federated graph schema through natural language commands.

This guide will help you understand how to give your AutoGen 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.

Also integrate Grafbase with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Grafbase
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Grafbase tools
  • Run a live chat loop where you ask the agent to perform Grafbase operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

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 step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Grafbase account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
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 python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Grafbase via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Grafbase connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Grafbase session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["grafbase"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Grafbase tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Grafbase assistant agent with MCP tools
    agent = AssistantAgent(
        name="grafbase_assistant",
        description="An AI assistant that helps with Grafbase operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Grafbase tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Grafbase related question or task to the agent.\n")

# Conversation loop
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")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Grafbase tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Grafbase and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Grafbase session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["grafbase"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Grafbase assistant agent with MCP tools
        agent = AssistantAgent(
            name="grafbase_assistant",
            description="An AI assistant that helps with Grafbase operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Grafbase related question or task to the agent.\n")

        # Conversation loop
        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")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You now have an Autogen assistant wired into Grafbase through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Grafbase, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

Every Grafbase action and event your agent gets out of the box.

Add Zitadel Redirect URI

Add a redirect URI to Zitadel OAuth configuration in Grafbase.

Assign Team Role

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

Delete Grafbase API Key

Delete an existing Grafbase API key (access token) by ID.

Delete Grafbase Audit Log

Tool to delete a specific Grafbase audit log entry.

Delete Extension

Tool to delete a Grafbase extension configuration by its unique ID.

Delete MCP Server

Tool to delete a Grafbase MCP server configuration by its unique ID.

Delete Grafbase Subgraph

Tool to delete a subgraph from a Grafbase federated graph.

Delete Schema Check

Attempt to delete a schema check from the Grafbase platform.

Delete Grafbase Team

Tool to delete a team from the Grafbase organization.

Disable MCP Server

Disable the Model Context Protocol (MCP) server for a Grafbase project.

Enable Grafbase MCP Server

Enable the Model Context Protocol (MCP) server on a Grafbase gateway.

Get Grafbase Audit Log

Tool to retrieve a specific Grafbase audit log entry by searching organization activity.

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

Tool to retrieve details about a specific Grafbase invitation by ID.

Get Notifications Inbox Messages

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

Get Grafbase Schema Check

Retrieve details of a specific schema check by its ID.

Get Subgraph Schema

Retrieves the GraphQL SDL schema for a specific subgraph by name.

List API Keys

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

List Grafbase Audit Logs

Tool to list audit logs for Grafbase organizations.

List Extensions

Tool to list all extensions configured for a Grafbase project.

List MCP Servers

Check MCP server configuration status for a Grafbase gateway.

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

Tool to list published subgraphs in your Grafbase federated graphs.

Mark Notifications as Read

Tool to mark Grafbase notifications as read.

Remove Graph Owner

Tool to remove an owner from a Grafbase graph.

FRAMEWORKS

How to build Grafbase MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Grafbase MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Grafbase MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Grafbase MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Grafbase MCP with Claude Cowork

Codex logo

Codex

Use Grafbase MCP with Codex

OpenClaw logo

OpenClaw

Use Grafbase MCP with OpenClaw

Hermes logo

Hermes

Use Grafbase MCP with Hermes

CLI logo

CLI

Use Grafbase MCP with CLI

Google ADK logo

Google ADK

Use Grafbase MCP with Google ADK

LangChain logo

LangChain

Use Grafbase MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Grafbase MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Grafbase MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Grafbase MCP with LlamaIndex

CrewAI logo

CrewAI

Use Grafbase MCP with CrewAI

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. Autogen 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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A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

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As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

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Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

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With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

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