Grafbase with LlamaIndex

How to integrate Grafbase MCP with LlamaIndex

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Introduction Also integrate Grafbase with TL;DR What is LlamaIndex What is the Grafbase MCP server Supported Tools & Triggers Creating MCP Server - Stand-alone vs Composio SDK Step-by-step Guide Complete Code Conclusion How to build Grafbase MCP Agent with another framework Explore Other Toolkits FAQ

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Introduction

This guide walks you through connecting Grafbase to LlamaIndex 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 LlamaIndex 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 SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenClaw Hermes CLI Google ADK LangChain Vercel AI SDK Mastra AI CrewAI

TL;DR

Here's what you'll learn:

Set your OpenAI and Composio API keys
Install LlamaIndex and Composio packages
Create a Composio Tool Router session for Grafbase
Connect LlamaIndex to the Grafbase MCP server
Build a Grafbase-powered agent using LlamaIndex
Interact with Grafbase through natural language

What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.

Key features include:

ReAct Agent: Reasoning and acting pattern for tool-using agents
MCP Tools: Native support for Model Context Protocol
Context Management: Maintain conversation context across interactions
Async Support: Built 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.

Supported Tools & Triggers

Tools

Add Zitadel Redirect URIAdd a redirect URI to Zitadel OAuth configuration in Grafbase.

Assign Team RoleTool to assign a role to a team member in Grafbase.

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

Delete Grafbase Audit LogTool to delete a specific Grafbase audit log entry.

Delete ExtensionTool to delete a Grafbase extension configuration by its unique ID.

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

Delete Grafbase SubgraphTool to delete a subgraph from a Grafbase federated graph.

Delete Schema CheckAttempt to delete a schema check from the Grafbase platform.

Delete Grafbase TeamTool to delete a team from the Grafbase organization.

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

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

Get Grafbase Audit LogTool to retrieve a specific Grafbase audit log entry by searching organization activity.

Get Extension by NameTool to retrieve a Grafbase extension by its name.

Get Extension Version By Name And VersionTool to retrieve details of a specific Grafbase extension version by name and version.

Get Federated SchemaRetrieves the composed federated graph schema from Grafbase in SDL format.

Get Grafbase InvitationTool to retrieve details about a specific Grafbase invitation by ID.

Get Notifications Inbox MessagesTool to retrieve notifications inbox messages for the authenticated Grafbase user.

Get Grafbase Schema CheckRetrieve details of a specific schema check by its ID.

Get Subgraph SchemaRetrieves the GraphQL SDL schema for a specific subgraph by name.

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

List Grafbase Audit LogsTool to list audit logs for Grafbase organizations.

List ExtensionsTool to list all extensions configured for a Grafbase project.

List MCP ServersCheck MCP server configuration status for a Grafbase gateway.

List Grafbase Schema ChecksList schema checks for a Grafbase graph.

List Grafbase SchemasTool to list all schemas in the Grafbase schema registry.

List Grafbase SubgraphsTool to list published subgraphs in your Grafbase federated graphs.

Mark Notifications as ReadTool to mark Grafbase notifications as read.

Remove Graph OwnerTool to remove an owner from a Grafbase graph.

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:

Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before you begin, make sure you have:

Python 3.8/Node 16 or higher installed
A Composio account with the API key
An OpenAI API key
A Grafbase account and project
Basic familiarity with async Python/Typescript

Getting API Keys for OpenAI, Composio, and Grafbase

OpenAI API key (OPENAI_API_KEY)

Go to the OpenAI dashboard
Create an API key if you don't have one
Assign it to OPENAI_API_KEY in .env

Composio API key and user ID

Log into the Composio dashboard
Copy your API key from Settings
- Use this as COMPOSIO_API_KEY
Pick a stable user identifier (email or ID)
- Use this as COMPOSIO_USER_ID

Installing dependencies

pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv

Create a new Python project and install the necessary dependencies:

composio-llamaindex: Composio's LlamaIndex integration
llama-index: Core LlamaIndex framework
llama-index-llms-openai: OpenAI LLM integration
llama-index-tools-mcp: MCP client for LlamaIndex
python-dotenv: Environment variable management

Set environment variables

bash

OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id

Create a .env file in your project root:

These credentials will be used to:

Authenticate with OpenAI's GPT-5 model
Connect to Composio's Tool Router
Identify your Composio user session for Grafbase access

Import modules

import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

Create a new file called grafbase_llamaindex_agent.py and import the required modules:

Key imports:

asyncio: For async/await support
Composio: Main client for Composio services
LlamaIndexProvider: Adapts Composio tools for LlamaIndex
ReActAgent: LlamaIndex's reasoning and action agent
BasicMCPClient: Connects to MCP endpoints
McpToolSpec: Converts MCP tools to LlamaIndex format

Load environment variables and initialize Composio

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")

What's happening:

This ensures missing credentials cause early, clear errors before the agent attempts to initialise.

Create a Tool Router session and build the agent function

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["grafbase"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Grafbase actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Grafbase actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)

What's happening here:

We create a Composio client using your API key and configure it with the LlamaIndex provider
We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, grafbase)
The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
LlamaIndex will connect to this endpoint to dynamically discover and use the available Grafbase tools.
The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.

Create an interactive chat loop

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

What's happening here:

We're creating a direct terminal interface to chat with your Grafbase database
The LLM's responses are streamed to the CLI for faster interaction.
The agent uses context to maintain conversation history
You can type 'quit' or 'exit' to stop the chat loop gracefully
Agent responses and any errors are displayed in a clear, readable format

Define the main entry point

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

What's happening here:

We're orchestrating the entire application flow
The agent gets built with proper error handling
Then we kick off the interactive chat loop so you can start talking to Grafbase

Run the agent

npx ts-node llamaindex-agent.ts

When prompted, authenticate and authorise your agent with Grafbase, then start asking questions.

Complete Code

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

import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["grafbase"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Grafbase actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Grafbase actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

Conclusion

You've successfully connected Grafbase to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:

Tool Router dynamically exposes Grafbase tools through an MCP endpoint
LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
The agent becomes more capable without increasing prompt size
Async Python provides clean, efficient execution of agent workflows

You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

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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 LlamaIndex?

Yes, you can. LlamaIndex 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.

Used by agents from

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We handle tool reliability, observability, and security so you never have to second-guess an agent action.

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Harsha GaddipatiCo-founder, Slashy

Karan skipped his own birthday party to fix our critical issue. It was 10 pm and he diverted his Waymo to help us instead. This really sets the bar, shows you the commitment you need to have when users rely on your software.

Abhi AryaCo-founder, Opennote

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 has immensely helped in keeping new users on the platform.

Nirman DaveCEO, Zams

We chose Composio over Pipedream because it delivered depth where it mattered. It supported niche tools and tricky edge cases that other platforms simply ignored. Giving us confidence to scale without compromising.

Ryan YuFounder, Extra Thursday

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

Tomisin JenrolaFounder & CEO, SwarmZero

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

Jerome LeclancheCo-Founder, Ingram Technologies

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.

Harsha GaddipatiCo-founder, Slashy

Abhi AryaCo-founder, Opennote

Nirman DaveCEO, Zams

Ryan YuFounder, Extra Thursday

Tomisin JenrolaFounder & CEO, SwarmZero

Jerome LeclancheCo-Founder, Ingram Technologies

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.

Harsha GaddipatiCo-founder, Slashy

Abhi AryaCo-founder, Opennote

Nirman DaveCEO, Zams

Ryan YuFounder, Extra Thursday

Tomisin JenrolaFounder & CEO, SwarmZero

Jerome LeclancheCo-Founder, Ingram Technologies

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.

How to integrate Grafbase MCP with LlamaIndex

Table of Contents

Connect Grafbase without Auth hassles

Introduction

Also integrate Grafbase with

TL;DR

What is LlamaIndex?

What is the Grafbase MCP server, and what's possible with it?

Supported Tools & Triggers

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

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI, Composio, and Grafbase

Installing dependencies

Set environment variables

Import modules

Load environment variables and initialize Composio

Create a Tool Router session and build the agent function

Create an interactive chat loop

Define the main entry point

Run the agent

Complete Code

Conclusion

How to build Grafbase MCP Agent with another framework

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

OpenClaw

Hermes

CLI

Google ADK

LangChain

Vercel AI SDK

Mastra AI

CrewAI

Explore Other Toolkits

Supabase

Codeinterpreter

GitHub

FAQ

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

Can I use Tool Router MCP with LlamaIndex?

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

How safe is my data with Composio Tool Router?

Used by agents from

Never worry about agent reliability