Set up AI assistants to access your Lemonado data using the Model Context Protocol (MCP)

Connect AI Tools to Your Data

Connect your favorite AI assistants to Lemonado using the Model Context Protocol (MCP). This allows AI tools to securely query and analyze your business data using natural language.

Client Guides for AI Tools

AI Assistants

Claude (Desktop & Web) - Anthropic's AI assistant
ChatGPT - OpenAI's ChatGPT with custom actions
OpenAI Agent Builder - Build custom AI agents with data access
Cursor - AI-powered code editor
Windsurf - Next-generation IDE with AI
Cody - Sourcegraph's AI coding assistant

Automation Tools

n8n - Workflow automation with AI capabilities

Quick Setup

1. Create an AI Connector

First, create an AI Connector in Lemonado:

Navigate to AI Connectors in your Lemonado dashboard
Click Create New Connector
Name your connector (e.g., "Production Data Access")
Select the data sources this connector can access
Choose your authentication method:
- OAuth: Best for web-based tools like ChatGPT
- Bearer Token: Best for desktop apps like Claude Desktop

2. Get Your Connection Details

After creating your connector, you'll receive:

MCP Server URL: https://api.lemonado.ai/mcp/your-connector-id
Authentication Token or OAuth Credentials

3. Configure Your AI Tool

Each AI tool has its own configuration process. Click on your tool above for detailed setup instructions.

How MCP Works

The Model Context Protocol (MCP) creates a secure bridge between your data in Lemonado and AI tools:

AI Tool sends a natural language query
MCP Server translates the query into SQL
Lemonado executes the query with proper permissions
Results are returned to the AI tool for analysis

Security Features

Granular Permissions: Control exactly which data each connector can access
Read-Only Access: AI tools can only query data, not modify it
Audit Logging: Every query is logged for security and compliance
Token Rotation: Bearer tokens can be regenerated at any time
OAuth Scopes: Fine-grained control for OAuth-based connections

Common Use Cases

Business Intelligence

Ask questions like:

"What were our top revenue drivers last quarter?"
"Show me customer churn trends by segment"
"Compare sales performance across regions"

Customer Support

"Find all support tickets from enterprise customers"
"What are the most common customer complaints?"
"Show unresolved issues older than 48 hours"

Development & Operations

"Generate a SQL query to find duplicate records"
"What database tables have the most rows?"
"Show me the schema for the orders table"

Best Practices

Create Separate Connectors for different use cases (e.g., one for customer data, another for financial data)
Use Descriptive Names for your connectors to easily identify their purpose
Regularly Review Access Logs to monitor how AI tools are using your data
Rotate Tokens Periodically for enhanced security
Start with Limited Access and gradually expand permissions as needed