How to integrate Grafbase MCP with CrewAI

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Introduction

This guide walks you through connecting Grafbase to CrewAI 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, enable the mcp server for my project through natural language commands.

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

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Grafbase connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Grafbase
  • Build a conversational loop where your agent can execute Grafbase operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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.

Supported Tools & Triggers

Tools
Delete Grafbase API KeyTool to delete an existing API key.
Delete Grafbase Audit LogTool to delete a specific Grafbase audit log entry.
Delete ExtensionTool to delete an extension configuration.
Delete MCP ServerTool to delete a Grafbase MCP server configuration by its unique ID.
Delete Grafbase SchemaTool to delete a Grafbase schema.
Delete Schema CheckTool to delete a Grafbase schema check.
Disable MCP serverTool to disable the Model Context Protocol server.
Enable Grafbase MCP ServerTool to enable the Model Context Protocol (MCP) server for a Grafbase project.
Get Grafbase Audit LogTool to retrieve a specific Grafbase audit log entry.
Get Federated SchemaTool to retrieve the composed federated graph schema.
Get Grafbase Schema CheckTool to retrieve the result of a schema check by its ID.
Get Subgraph SchemaTool to retrieve the GraphQL SDL of a specific subgraph.
List API KeysTool to list all API keys for a project.
List Grafbase Audit LogsTool to list all audit logs for a project.
List ExtensionsTool to list all extensions configured for a Grafbase project.
List MCP ServersTool to list all MCP servers configured for a project.
List Grafbase Schema ChecksTool to list all Grafbase schema checks for a project.
List Grafbase SchemasTool to list all Grafbase schemas.
List Grafbase SubgraphsTool to list published subgraphs in a branch.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router 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 Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router 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

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Grafbase connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

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.

Install dependencies

bash
pip install composio crewai crewai-tools python-dotenv
What's happening:
  • composio connects your agent to Grafbase via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools includes MCP helpers
  • python-dotenv loads environment variables from .env

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_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional import if you plan to adapt tools
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Grafbase MCP URL

Create a Composio Tool Router session for Grafbase

python
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:
  • You create a Grafbase only session through Composio
  • Composio returns an MCP HTTP URL that exposes Grafbase tools

Configure the LLM

python
llm = LLM(
    model="gpt-5-mini",
    api_key=os.getenv("OPENAI_API_KEY"),
)
What's happening:
  • CrewAI will call this LLM for planning and responses
  • You can swap in a different model if needed

Attach the MCP server and create the agent

python
toolkit_agent = Agent(
    role="Grafbase Assistant",
    goal="Help users interact with Grafbase through natural language commands",
    backstory=(
        "You are an expert assistant with access to Grafbase tools. "
        "You can perform various Grafbase operations on behalf of the user."
    ),
    mcps=[
        MCPServerHTTP(
            url=url,
            streamable=True,
            cache_tools_list=True,
            headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
        ),
    ],
    llm=llm,
    verbose=True,
    max_iter=10,
)
What's happening:
  • MCPServerHTTP connects the agent to the Grafbase MCP endpoint
  • cache_tools_list saves a tools catalog for faster subsequent runs
  • verbose helps you see what the agent is doing

Add a REPL loop with Task and Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to perform Grafbase operations.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Based on the conversation history:\n{conversation_context}\n\n"
            f"Current user request: {user_input}\n\n"
            f"Please help the user with their Grafbase related request."
        ),
        expected_output="A helpful response addressing the user's request",
        agent=toolkit_agent,
    )

    crew = Crew(
        agents=[toolkit_agent],
        tasks=[task],
        verbose=False,
    )

    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's happening:
  • You build a simple chat loop and keep a running context
  • Each user turn becomes a Task handled by the same agent
  • Crew executes the task and returns a response

Run the application

python
if __name__ == "__main__":
    main()
What's happening:
  • Standard Python entry point so you can run python crewai_grafbase_agent.py

Complete Code

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

python
# file: crewai_grafbase_agent.py
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()

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 LLM
    llm = LLM(
        model="gpt-5-mini",
        api_key=os.getenv("OPENAI_API_KEY"),
    )

    # Create Grafbase assistant agent
    toolkit_agent = Agent(
        role="Grafbase Assistant",
        goal="Help users interact with Grafbase through natural language commands",
        backstory=(
            "You are an expert assistant with access to Grafbase tools. "
            "You can perform various Grafbase operations on behalf of the user."
        ),
        mcps=[
            MCPServerHTTP(
                url=url,
                streamable=True,
                cache_tools_list=True,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
            ),
        ],
        llm=llm,
        verbose=True,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Try asking the agent to perform Grafbase operations.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Based on the conversation history:\n{conversation_context}\n\n"
                f"Current user request: {user_input}\n\n"
                f"Please help the user with their Grafbase related request."
            ),
            expected_output="A helpful response addressing the user's request",
            agent=toolkit_agent,
        )

        crew = Crew(
            agents=[toolkit_agent],
            tasks=[task],
            verbose=False,
        )

        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

if __name__ == "__main__":
    main()

Conclusion

You now have a CrewAI agent connected to Grafbase through Composio's Tool Router. The agent can perform Grafbase operations through natural language commands. Next steps:
  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

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FAQ

What are the differences in Tool Router MCP and Grafbase MCP?

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.

Can I use Tool Router MCP with CrewAI?

Yes, you can. CrewAI 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.

Can I manage the permissions and scopes for Grafbase while using Tool Router?

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.

How safe is my data with Composio Tool Router?

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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