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Author SHA1 Message Date
Wenxin Du
c65f26b21a Merge branch 'main' into fix-redis-doc 2026-01-13 13:20:14 -05:00
duwenxin99
ea16e25e41 docs: fix redis array sample 2026-01-13 11:29:24 -05:00
3 changed files with 4 additions and 148 deletions

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@@ -30,6 +30,10 @@ following config for example:
- name: userNames
type: array
description: The user names to be set.
items:
name: userName # the item name doesn't matter but it has to exist
type: string
description: username
```
If the input is an array of strings `["Alice", "Sid", "Bob"]`, The final command

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@@ -1,7 +0,0 @@
---
title: "Neo4j"
type: docs
weight: 1
description: >
How to get started with Toolbox using Neo4j.
---

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@@ -1,141 +0,0 @@
---
title: "Quickstart (MCP with Neo4j)"
type: docs
weight: 1
description: >
How to get started running Toolbox with MCP Inspector and Neo4j as the source.
---
## Overview
[Model Context Protocol](https://modelcontextprotocol.io) is an open protocol that standardizes how applications provide context to LLMs. Check out this page on how to [connect to Toolbox via MCP](../../how-to/connect_via_mcp.md).
## Step 1: Set up your Neo4j Database and Data
In this section, you'll set up a database and populate it with sample data for a movies-related agent. This guide assumes you have a running Neo4j instance, either locally or in the cloud.
. **Populate the database with data.**
To make this quickstart straightforward, we'll use the built-in Movies dataset available in Neo4j.
. In your Neo4j Browser, run the following command to create and populate the database:
+
```cypher
:play movies
````
. Follow the instructions to load the data. This will create a graph with `Movie`, `Person`, and `Actor` nodes and their relationships.
## Step 2: Install and configure Toolbox
In this section, we will install the MCP Toolbox, configure our tools in a `tools.yaml` file, and then run the Toolbox server.
. **Install the Toolbox binary.**
The simplest way to get started is to download the latest binary for your operating system.
. Download the latest version of Toolbox as a binary:
\+
```bash
export OS="linux/amd64" # one of linux/amd64, darwin/arm64, darwin/amd64, or windows/amd64
curl -O [https://storage.googleapis.com/genai-toolbox/v0.16.0/$OS/toolbox](https://storage.googleapis.com/genai-toolbox/v0.16.0/$OS/toolbox)
```
+
. Make the binary executable:
\+
```bash
chmod +x toolbox
```
. **Create the `tools.yaml` file.**
This file defines your Neo4j source and the specific tools that will be exposed to your AI agent.
\+
{{\< notice tip \>}}
Authentication for the Neo4j source uses standard username and password fields. For production use, it is highly recommended to use environment variables for sensitive information like passwords.
{{\< /notice \>}}
\+
Write the following into a `tools.yaml` file:
\+
```yaml
sources:
my-neo4j-source:
kind: neo4j
uri: bolt://localhost:7687
user: neo4j
password: my-password # Replace with your actual password
tools:
search-movies-by-actor:
kind: neo4j-cypher
source: my-neo4j-source
description: "Searches for movies an actor has appeared in based on their name. Useful for questions like 'What movies has Tom Hanks been in?'"
parameters:
- name: actor_name
type: string
description: The full name of the actor to search for.
statement: |
MATCH (p:Person {name: $actor_name}) -[:ACTED_IN]-> (m:Movie)
RETURN m.title AS title, m.year AS year, m.genre AS genre
get-actor-for-movie:
kind: neo4j-cypher
source: my-neo4j-source
description: "Finds the actors who starred in a specific movie. Useful for questions like 'Who acted in Inception?'"
parameters:
- name: movie_title
type: string
description: The exact title of the movie.
statement: |
MATCH (p:Person) -[:ACTED_IN]-> (m:Movie {title: $movie_title})
RETURN p.name AS actor
```
. **Start the Toolbox server.**
Run the Toolbox server, pointing to the `tools.yaml` file you created earlier.
\+
```bash
./toolbox --tools-file "tools.yaml"
```
## Step 3: Connect to MCP Inspector
. **Run the MCP Inspector:**
\+
```bash
npx @modelcontextprotocol/inspector
```
. Type `y` when it asks to install the inspector package.
. It should show the following when the MCP Inspector is up and running (please take note of `<YOUR_SESSION_TOKEN>`):
\+
```bash
Starting MCP inspector...
⚙️ Proxy server listening on localhost:6277
🔑 Session token: <YOUR_SESSION_TOKEN>
Use this token to authenticate requests or set DANGEROUSLY_OMIT_AUTH=true to disable auth
🚀 MCP Inspector is up and running at:
http://localhost:6274/?MCP_PROXY_AUTH_TOKEN=<YOUR_SESSION_TOKEN>
```
1. Open the above link in your browser.
1. For `Transport Type`, select `Streamable HTTP`.
1. For `URL`, type in `http://127.0.0.1:5000/mcp`.
1. For `Configuration` -\> `Proxy Session Token`, make sure `<YOUR_SESSION_TOKEN>` is present.
1. Click `Connect`.
1. Select `List Tools`, you will see a list of tools configured in `tools.yaml`.
1. Test out your tools here\!