Securely Chat with Your Data

💬 Overview

This module shows you how to connect any AI agent (ChatGPT, Claude, Cursor, Copilot, or a custom tool) to your enterprise database through DreamFactory. Once connected, anyone in your organization can ask plain English questions about company data and get instant answers.

No SQL knowledge. No code. No waiting for a data analyst to run a report. Just open your AI agent, ask a question, and get the data you need.

What You'll Build

By the end of this guide, you'll have:

• A DreamFactory MCP service connected to your database
• OAuth-based authentication for secure AI agent access
• An AI agent (ChatGPT, Claude, Cursor, etc.) querying live enterprise data
• RBAC policies controlling exactly which data the AI can access
• Full audit logging of every query the AI makes

Who This Is For

• Business users who want to query company data without SQL
• IT administrators setting up secure AI access to databases
• Data teams looking to democratize access to reports and metrics
• Developers evaluating AI-to-database integration patterns

📧 The Scenario

Your CEO sends an email:

Normally, this triggers a chain: you email the data team, they write SQL queries, pull the data into a spreadsheet, format it, and send it back. That takes hours, maybe days.

With DreamFactory and an AI agent, the answer takes about 30 seconds:

1. Open ChatGPT (or Claude, Cursor, or any AI agent)
2. Ask: "Show me a breakdown of customers by region"
3. Get a formatted table with the data, pulled live from your database
4. Follow up: "Which of those regions had the most sales last quarter?"
5. Get the refined answer instantly

The AI never touches your database directly. Every query flows through DreamFactory's security layer, which enforces access controls, logs every request, and rate-limits usage.

🏗️ How It Works

The architecture has three layers. The AI agent never connects directly to your database. DreamFactory sits in the middle, acting as an AI Data Gateway.

What the AI Data Gateway Does

1 Create an MCP Service

1

Enable the MCP Server in DreamFactory

~1 min

DreamFactory 7.4+ includes a built-in MCP (Model Context Protocol) server. MCP is the standard protocol that AI agents use to discover and interact with external tools, in this case your database.

Navigate to Services > Create > MCP in your DreamFactory admin panel:

Configure the service:

• Service Name: Choose a descriptive name (e.g., sales-data-mcp)
• Label: Human-readable label for the admin panel
• Description: Brief description of what data this service exposes
• Active: Toggle on to enable the service

2 Configure Your Database Connection

2

Connect DreamFactory to Your Database

~2 min

If you haven't already connected a database to DreamFactory, go to Services > Create > Database and add your connection.

DreamFactory supports all major databases:

Database	Connection Type	Notes
SQL Databases
MySQL / MariaDB	Native driver	Most common for web apps
PostgreSQL	Native driver	Advanced features, JSON support
SQL Server	Native driver	Enterprise standard, Active Directory integration
Oracle	OCI driver	Enterprise, requires Oracle client
SQLite	File-based	Great for demos and prototyping
IBM DB2 / Firebird	Native driver	Legacy enterprise databases
NoSQL Databases
MongoDB	Native driver	NoSQL document store
DynamoDB	AWS SDK	AWS managed NoSQL, key-value and document
Cassandra / CouchDB	Native driver	Distributed NoSQL stores
Cloud / Data Warehouse
Snowflake	ODBC/Native	Cloud data warehouse, analytics workloads
AWS Redshift	PostgreSQL wire protocol	AWS columnar data warehouse
SAP HANA	ODBC driver	In-memory enterprise platform
Databricks	ODBC/JDBC	Lakehouse analytics platform
Azure SQL	Native driver	Azure-managed SQL Server

Once connected, DreamFactory auto-discovers your schema (tables, columns, relationships). The MCP service will expose these as tools that your AI agent can use. Beyond databases, DreamFactory can also expose file storage services (such as S3, Azure Blob, and SFTP) through MCP, giving your AI agent access to documents and files alongside structured data.

3 Set Up Authentication

3

Configure OAuth for AI Agent Access

~2 min

Your AI agent needs credentials to authenticate with DreamFactory. The recommended approach is OAuth 2.0, which gives you token-based access with expiration and revocation.

Create a Role for AI Access

First, create a role that defines what data the AI agent can see. Navigate to Roles in the admin panel:

Best practices for AI agent roles:

• Read-only access: AI agents should never be able to INSERT, UPDATE, or DELETE
• Table filtering: Only expose the tables relevant to the use case
• Column masking: Hide sensitive columns (SSN, credit card numbers, etc.)
• Row-level filtering: Restrict data by business unit, region, or user context

Generate OAuth Credentials

Create an API key and assign it to the AI role. The AI agent will use this key to authenticate via OAuth:

OAuth Flow Copy

# 1. AI agent requests access token
POST /oauth/token
{
  "grant_type": "client_credentials",
  "client_id": "your-ai-agent-client-id",
  "client_secret": "your-client-secret"
}

# 2. DreamFactory returns a scoped token
{
  "access_token": "eyJhbGciOiJSUzI1NiIs...",
  "token_type": "Bearer",
  "expires_in": 3600
}

# 3. AI agent uses token for MCP requests
# Token inherits the role's access policies

4 Connect Your AI Agent

4

Point Your AI Agent at DreamFactory

~1 min

The final step is connecting your AI agent to the DreamFactory MCP endpoint. You'll need the MCP server URL and OAuth credentials from your DreamFactory configuration:

The exact connection steps depend on your AI agent:

ChatGPT (Custom GPTs)

In the GPT Builder, add your DreamFactory instance as an MCP server action. ChatGPT will automatically discover the available tools (your database tables) and use them to answer questions.

Claude Desktop

Add the MCP server to your Claude Desktop configuration:

JSON claude_desktop_config.json Copy

{
  "mcpServers": {
    "dreamfactory-sales": {
      "url": "https://your-instance.dreamfactory.com/mcp/my-ai-service",
      "auth": {
        "type": "oauth2",
        "client_id": "your-client-id",
        "client_secret": "your-client-secret"
      }
    }
  }
}

Any MCP-Compatible Agent

Any tool that supports MCP can connect to DreamFactory. The MCP protocol is standardized, so your DreamFactory endpoint works the same way regardless of which AI agent connects to it.

🔍 Your First Query

With everything connected, open your AI agent and ask a natural language question about your data. Here's what a typical conversation looks like:

You:    How many customers do we have in each region?

AI:     I'll query the customers table grouped by region.

         | Region        | Customer Count |
         |---------------|---------------|
         | North America | 1,247         |
         | Europe        | 893           |
         | Asia Pacific  | 634           |
         | Latin America | 412           |
         | Middle East   | 198           |

         You have 3,384 total customers across 5 regions.
         North America leads with 36.8% of all customers.

The AI agent translated your plain English question into a SQL query, sent it through DreamFactory (which validated it against your access policies), and returned the results in a readable format.

What Happened Behind the Scenes

🔄 Refining Results Through Conversation

The real power of chatting with your data is the ability to refine. You don't get a static report; you have a conversation. Each follow-up question narrows the results further.

# Query 1: Broad overview
You:    Show me all customers

AI:     Found 134 customers across the database.

# Query 2: Filter by activity
You:    Which of those have active subscriptions?

AI:     89 customers have active subscriptions.

# Query 3: Focus on high value
You:    Show me the ones with annual revenue over $100K

AI:     32 customers with active subscriptions
         and annual revenue exceeding $100,000.

# Query 4: Actionable insight
You:    Sort by renewal date - which ones renew this quarter?

AI:     8 high-value customers renewing in Q1:
         [detailed table with names, revenue, renewal dates]

In four conversational turns, you went from 134 customers to 8 actionable renewal opportunities, information that would have taken a data analyst hours to compile into a report.

🛡️ Security Controls

Security isn't a bolt-on feature; it's the core reason DreamFactory exists in this architecture. Here's how every query is protected:

Role-Based Access Control (RBAC)

DreamFactory's RBAC system controls exactly what data the AI agent can access:

Audit Logging

Every request the AI agent makes is logged with:

• Timestamp and request ID
• Authenticated user/role identity
• The exact query executed
• Response data summary (row count, columns returned)
• Execution time and status code

Rate Limiting

Prevent AI agents from overwhelming your database with too many requests:

• Per-role limits: Set maximum requests per minute/hour for AI agent roles
• Per-service limits: Cap the load on specific database services
• Burst protection: Prevent sudden spikes from runaway AI loops

✅ Best Practices

Security

• Least privilege: Give AI agents the minimum access they need: read-only, specific tables only
• Separate roles per use case: Create distinct roles for sales analytics, customer support, finance, etc.
• Rotate credentials: Use short-lived OAuth tokens and rotate client secrets regularly
• Monitor audit logs: Review AI query patterns weekly to catch anomalies

Performance

• Limit result sets: Configure maximum row counts to prevent the AI from pulling entire tables
• Use views or stored procedures: Pre-aggregate complex data so the AI doesn't need to join many tables (Module 04 covers stored procedures)
• Index frequently queried columns: If the AI often filters by region or date, ensure those columns are indexed
• Cache common queries: DreamFactory's caching layer reduces repeated database hits

User Experience

• Describe your data clearly: Table and column names should be human-readable (the AI uses them for context)
• Provide table descriptions: DreamFactory lets you add descriptions to services and tables, and the AI reads these to understand your schema
• Start broad, then refine: Encourage users to ask overview questions first, then drill down

🔧 Troubleshooting

Common Issues

Getting Help

• DreamFactory Docs: dreamfactory.com/docs
• Community Forum: community.dreamfactory.com
• Next Module: Module 02: Setting Up Your MCP Server covers connecting AI agents to DreamFactory through the Model Context Protocol

🎬 Watch the Full Demo

DreamFactory CTO Kevin McGahey demonstrates everything in this module, from setup to live queries, in under 12 minutes.