How to integrate Neo4J MCP with Mastra AI

This guide walks you through connecting Neo4J to Mastra AI using the Composio tool router. By the end, you'll have a working Neo4J agent that can run cypher queries on customer graph, find shortest paths between accounts, create nodes for new transactions through natural language commands. This guide will help you understand how to give your Mastra AI agent real control over a Neo4J account through Composio's Neo4J MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Neo4J is a graph database platform for storing and querying connected data. Use it to model relationships, run Cypher queries, and power real-time graph analytics.

21 Tools

Introduction

This guide walks you through connecting Neo4J to Mastra AI using the Composio tool router. By the end, you'll have a working Neo4J agent that can run cypher queries on customer graph, find shortest paths between accounts, create nodes for new transactions through natural language commands.

This guide will help you understand how to give your Mastra AI agent real control over a Neo4J account through Composio's Neo4J MCP server.

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

Also integrate Neo4J with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKLlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Set up your environment so Mastra, OpenAI, and Composio work together
  • Create a Tool Router session in Composio that exposes Neo4J tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Neo4J tool definitions and attach them as a toolset
  • Build a Mastra agent that can reason, call tools, and return structured results
  • Run an interactive CLI where you can chat with your Neo4J agent

What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.

Key features include:

  • MCP Client: Built-in support for Model Context Protocol servers
  • Toolsets: Organize tools into logical groups
  • Step Callbacks: Monitor and debug agent execution
  • OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

What is the Neo4J MCP server, and what's possible with it?

The Neo4J MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Neo4J account. It provides structured and secure access to your Neo4J Aura resources, so your agent can manage database instances, handle snapshots, review projects and users, monitor Graph Data Science sessions, and configure IP filters on your behalf.

  • Aura instance management: Have your agent list, create, inspect, update, or pause Neo4J Aura instances based on your infrastructure needs.
  • Snapshot and recovery operations: Direct your agent to create snapshots, review available backups, inspect snapshot details, or restore an Aura instance from a snapshot.
  • Project and user oversight: Let the agent list Aura projects, inspect project details, review project users, or retrieve information about an organization user.
  • Graph Data Science planning: Instruct your agent to list active Graph Data Science sessions or estimate session size from node counts, relationship counts, and algorithm categories.
  • Network access and agent review: Have your agent list Aura agents, review organization IP filters, or update an existing IP filter.

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:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key.
  • You need credits or a connected billing setup to use the models.
  • Store the key somewhere safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Go to Settings and copy your API key.
  • This key lets your Mastra agent talk to Composio and reach Neo4J through MCP.
3

Install dependencies

bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv

Install the required packages.

What's happening:

  • @composio/core is the Composio SDK for creating MCP sessions
  • @mastra/core provides the Agent class
  • @mastra/mcp is Mastra's MCP client
  • @ai-sdk/openai is the model wrapper for OpenAI
  • dotenv loads environment variables from .env
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_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 your requests to Composio
  • COMPOSIO_USER_ID tells Composio which user this session belongs to
  • OPENAI_API_KEY lets the Mastra agent call OpenAI models
5

Import libraries and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey as string,
});
What's happening:
  • dotenv/config auto loads your .env so process.env.* is available
  • openai gives you a Mastra compatible model wrapper
  • Agent is the Mastra agent that will call tools and produce answers
  • MCPClient connects Mastra to your Composio MCP server
  • Composio is used to create a Tool Router session
6

Create a Tool Router session for Neo4J

typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["neo4j"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Neo4J MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "neo4j" for Neo4J access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
7

Configure Mastra MCP client and fetch tools

typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
What's happening:
  • MCPClient takes an id for this client and a list of MCP servers
  • The headers property includes the x-api-key for authentication
  • getTools fetches the tool definitions exposed by the Neo4J toolkit
8

Create the Mastra agent

typescript
const agent = new Agent({
    name: "neo4j-mastra-agent",
    instructions: "You are an AI agent with Neo4J tools via Composio.",
    model: "openai/gpt-5",
  });
What's happening:
  • Agent is the core Mastra agent
  • name is just an identifier for logging and debugging
  • instructions guide the agent to use tools instead of only answering in natural language
  • model uses openai("gpt-5") to configure the underlying LLM
9

Set up interactive chat interface

typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\n");

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        neo4j: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • messages keeps the full conversation history in Mastra's expected format
  • agent.generate runs the agent with conversation history and Neo4J toolsets
  • maxSteps limits how many tool calls the agent can take in a single run
  • onStepFinish is a hook that prints intermediate steps for debugging

Complete Code

Here's the complete code to get you started with Neo4J and Mastra AI:

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({ apiKey: composioAPIKey as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["neo4j"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      neo4j: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "neo4j-mastra-agent",
    instructions: "You are an AI agent with Neo4J tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { neo4j: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();

Conclusion

You've built a Mastra AI agent that can interact with Neo4J through Composio's Tool Router. You can extend this further by:
  • Adding other toolkits like Gmail, Slack, or GitHub
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows
TOOLS

Supported Tools

Every Neo4J action and event your agent gets out of the box.

Aggregate Directors Count

Executes a directorsAggregate GraphQL query to count directors in Neo4j.

Create Neo4j Aura Instance

Creates a new Neo4j Aura instance with the specified configuration.

Create Neo4j Aura Snapshot

Create an on-demand snapshot of a Neo4j Aura instance.

Estimate GDS Session Size

Estimate the size of a new GDS (Graph Data Science) session based on node/relationship counts and algorithm categories.

Get Neo4j Aura Instance Details

Retrieves details for a specific Neo4j Aura instance using its unique instance ID.

Get Neo4j Aura Organization User

Retrieves details of a specific user in a Neo4j Aura organization.

Get Neo4j Aura Project Details

Retrieve details of a specific Neo4j Aura project (tenant).

Get Neo4j Aura Project Details (v1beta5)

Retrieve details of a specific Neo4j Aura project (tenant) using the v1beta5 API.

Get Neo4j Aura Snapshot Details

Retrieves details of a specific snapshot for a Neo4j Aura instance.

List Neo4j Aura Agents

List all agents belonging to a specific Neo4j Aura project.

List GDS Sessions

List all Graph Data Science (GDS) sessions for the authenticated Neo4j Aura account.

List Neo4j Aura Instances

Returns a list of Neo4j Aura instances.

List IP Filters

Returns a list of IP filters configured for a Neo4j Aura organization.

List Aura Projects

List all Aura projects (tenants) available to the authenticated user.

List Project Users

List all users in a specific Neo4j Aura project.

List Neo4j Aura Snapshots

Lists available snapshots for a Neo4j Aura instance.

Pause Neo4j Aura Instance

Pauses a Neo4j Aura instance.

Restore Neo4j Aura Instance from Snapshot

Restore a Neo4j Aura instance from a snapshot.

Update Neo4j Aura Instance

Updates a Neo4j Aura instance configuration.

Update Neo4j Aura Instance

Edits the configuration of a Neo4j Aura instance.

Update IP Filter

Updates an existing IP filter for a Neo4j Aura organization.

FRAMEWORKS

How to build Neo4J MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Neo4J MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Neo4J MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Neo4J MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Neo4J MCP with Claude Cowork

Codex logo

Codex

Use Neo4J MCP with Codex

OpenClaw logo

OpenClaw

Use Neo4J MCP with OpenClaw

Hermes logo

Hermes

Use Neo4J MCP with Hermes

CLI logo

CLI

Use Neo4J MCP with CLI

Google ADK logo

Google ADK

Use Neo4J MCP with Google ADK

LangChain logo

LangChain

Use Neo4J MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Neo4J MCP with Vercel AI SDK

LlamaIndex logo

LlamaIndex

Use Neo4J MCP with LlamaIndex

CrewAI logo

CrewAI

Use Neo4J MCP with CrewAI

FAQ

Frequently asked questions

With a standalone Neo4J MCP server, the agents and LLMs can only access a fixed set of Neo4J tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Neo4J and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Mastra 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 Neo4J tools.

Yes, absolutely. You can configure which Neo4J 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 Neo4J 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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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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