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Lemonado Logo

Lemonado MCP Server

The Lemonado Model Context Protocol (MCP) server at mcp.lemonado.io/mcp enables your AI agents to query data from marketing platforms, payment processors, and productivity tools such as Google Ads, Meta Ads, LinkedIn Ads, Google Analytics, Stripe, Google Sheets, and CSV files. The MCP can run SQL across these data sources.

Our Integrations

  • Google Ads
  • Meta Ads (Facebook/Instagram)
  • LinkedIn Ads
  • Google Analytics
  • Stripe
  • Google Sheets
  • CSV files
  • ...and more!

We continuously add new integrations to expand your data access capabilities.

View all integrations →

What You Can Ask Your AI

With Lemonado MCP, you can ask complex cross-platform questions like:

  • "Compare this week's Google Ads spend to our 30-day average"
  • "Which Meta Ads campaigns drove the most conversions last month?"
  • "Show me the top performing LinkedIn Ads by click-through rate"
  • "Calculate ROI for each marketing channel"
  • "What are the trends in cost per click across all ad platforms?"

Authentication

Lemonado MCP supports two authentication methods:

Bearer Token Authentication

Get a bearer token by registering at data.lemonado.io/signup. This method is ideal for:

  • Desktop applications (Claude Desktop, Cursor)
  • Direct API access
  • Testing and development

OAuth 2.0

Secure OAuth authentication is available for:

  • Web-based AI tools (ChatGPT, Claude Web)
  • Enterprise deployments
  • Multi-user environments

Installation

Requirements

  • A Lemonado account (Create free account →)
  • At least one data source connected in Lemonado
  • Claude, ChatGPT, n8n, or another MCP-compatible client
Install in Claude

Connect your Lemonado data to Claude using the Model Context Protocol (MCP). Choose your preferred Claude platform below.

Claude.ai (Web) - Browser-based

Prerequisites:

Setup Instructions:

  1. Go to claude.ai in your browser
  2. Click on Settings (usually found in the bottom left or profile menu)
  3. Navigate to the Connectors section
  4. Click Add custom connector
  5. Fill in the connector details:
    • Name: Lemonado
    • Remote MCP Server URL: https://mcp.lemonado.io/mcp
  6. Click Add to save the connector
  7. Click Connect to initiate the authentication process
  8. Follow the OAuth flow - a new browser tab will open for you to log in to Lemonado
  9. Once authenticated, return to Claude.ai - your connector should show as connected
  10. You can now use MCP tools in your Claude conversations

Claude Desktop - Native app

Prerequisites:

Setup Instructions:

  1. Open Claude Desktop application
  2. Click on your profile avatar in the bottom left corner
  3. Select Settings from the menu
  4. Navigate to the Connectors section
  5. Click Add custom connector
  6. Fill in the connector configuration:
    • Name: Lemonado
    • Remote MCP Server URL: https://mcp.lemonado.io/mcp
  7. Click Add to save the connector
  8. Click Connect to initiate authentication
  9. A new browser tab will open - log in to Lemonado if prompted
  10. Authorize the connection and return to Claude Desktop
  11. You can now use MCP tools in your Claude conversations

Claude Code - Terminal-based

Prerequisites:

Setup Instructions:

  1. Install Claude Code from the official Anthropic website if you haven't already
  2. Open Claude Code in your terminal: 
    claude
  3. Open the configuration file by running: 
    claude config edit
  4. Add the following MCP server configuration to your config file: 
    {
    "mcpServers": {
        "lemonado": {
            "command": "npx",
            "args": ["-y", "@modelcontextprotocol/server-fetch", "https://mcp.lemonado.io/mcp"],
            "env": {
                "MCP_AUTH_TYPE": "oauth",
                "MCP_OAUTH_PROVIDER": "lemonado"
            }
        }
    }
}
  5. Save the configuration file and restart Claude Code
  6. Start a new conversation - Claude Code will prompt you to authenticate
  7. Follow the OAuth flow in your browser to connect to Lemonado
  8. Once authenticated, you can query your Lemonado data directly in Claude Code

Troubleshooting:

  • Authentication Issues: If OAuth fails, try running claude config edit again and ensure the configuration is correct
  • Connection Problems: Verify that https://mcp.lemonado.io/mcp is accessible
  • No Data Available: Check that your Lemonado account has the necessary permissions and data sources connected
  • Configuration Not Loading: Restart Claude Code after saving the configuration file

Full Claude setup guide →

Install in ChatGPT Developer Mode

New in September 2025: OpenAI has released MCP support in ChatGPT Developer Mode, enabling direct access to your Lemonado data.

Overview

ChatGPT now supports the Model Context Protocol (MCP) through Developer Mode, allowing direct connection to your Lemonado AI Connectors.

Prerequisites

  • ChatGPT Plus or Pro subscription (required for Developer Mode)
  • Developer Mode enabled in ChatGPT settings
  • Lemonado account with at least one data source connected

Setup Instructions

Step 1: Enable Developer Mode

  1. Open ChatGPT in your web browser
  2. Click your profile picture → Settings
  3. Navigate to Connectors → Advanced
  4. Toggle on Developer mode (beta)

Step 2: Add Lemonado MCP Connector

  1. In the Connectors section, click Add custom connector
  2. Enter the connector details:
    • Name: Lemonado
    • Remote MCP Server URL: https://mcp.lemonado.io/mcp
  3. Click Connect
  4. You'll be redirected to Lemonado to authenticate
  5. Log in to your Lemonado account
  6. Select which AI Connector you want to use
  7. Authorize ChatGPT to access your data

Step 3: Verify Connection

After OAuth authentication completes, ChatGPT will have access to your selected AI Connector.

Step 4: Test the Connection

  1. Start a new chat in ChatGPT
  2. Click the paperclip icon or connectors button in the message box
  3. Select Lemonado from the list of available connectors
  4. Test with a query like: 
    "Show me a list of available data sources"

If successful, you'll see ChatGPT accessing your Lemonado data directly.

Capabilities

With MCP in Developer Mode, ChatGPT can:

Data Access:

  • Query any connected database or SaaS tool
  • Search and filter records
  • Generate reports and analytics
  • Access real-time synchronized data

Analysis & Insights:

  • Perform complex data analysis
  • Generate visualizations
  • Identify trends and patterns
  • Create custom reports

Example Usage

Data Analysis:

"Analyze campaign performance across Google Ads and Meta Ads for the last quarter"

Marketing Insights:

"Show me cost per click trends across all ad platforms"

Report Generation:

"Create a monthly marketing report comparing this month to last month, broken down by channel"

Trend Analysis:

"Identify seasonal patterns in our ad spend and predict next month's budget needs"

Security & Privacy

OAuth Authentication:

Lemonado uses OAuth for secure authentication:

  • No API keys to manage or expose
  • Credentials are never shared with ChatGPT
  • You control which AI Connector ChatGPT can access
  • Disable the connector anytime from your Lemonado dashboard

Data Access Control:

  • Configure permissions in your AI Connector settings
  • All access is read-only for security
  • Use data filtering to limit exposed information
  • Monitor all queries in your Lemonado audit logs

Troubleshooting

Connection Failed:

  1. Verify Developer Mode is enabled
  2. Ensure you completed OAuth authentication
  3. Check your AI Connector is active in Lemonado
  4. Try removing and re-adding the connector

Authentication Issues:

  • Clear browser cookies and try again
  • Ensure you're logged into the correct Lemonado account
  • Check if your AI Connector has been deleted or disabled

No Data Returned:

  • Verify your data sources are connected in Lemonado
  • Check if data sync has completed
  • Ensure your AI Connector has access to the data sources
  • Review query syntax and filters

Full ChatGPT setup guide →

Install in OpenAI Agent Builder

Secure MCP Integration: OpenAI Agent Builder now supports Model Context Protocol through secure token authentication, enabling direct access to your Lemonado data.

Overview

OpenAI Agent Builder allows you to create custom AI agents with access to external tools and data sources. By connecting Lemonado via MCP, your agents can query databases, SaaS tools, and analytics platforms in real-time.

Prerequisites

  • OpenAI account with access to Agent Builder
  • Active Lemonado AI Connector with MCP endpoint configured
  • API access token (generated from Lemonado)

Setup Instructions

Step 1: Generate Lemonado Access Token

  1. Log in to your Lemonado dashboard
  2. Navigate to your AI Connector settings
  3. Click Generate Access Token
  4. Copy the bearer token (it will only be shown once)
  5. Save it securely - this token never expires unless regenerated

Important: Store your access token securely. If compromised, regenerate it immediately from your Lemonado dashboard.

Step 2: Configure OpenAI Agent Builder

  1. Go to your agent in OpenAI Agent Builder
  2. Click Add Tool → MCP Server
  3. Choose + Server in the top right
  4. Fill in the server details:
    • URL: https://mcp.lemonado.io/mcp
    • Name: Lemonado
    • Description: Access your Lemonado data and analytics through MCP
    • Authentication: Access Token / API Key
  5. Paste your Lemonado bearer token in the authentication field
  6. Click Connect to save the configuration

Step 3: Test the Connection

In your agent's chat interface, try a test query:

"List all available data sources from Lemonado"

If successful, your agent will return information from your Lemonado AI Connector.

Capabilities

With Lemonado connected to your OpenAI agent, you can:

Data Access:

  • Query any connected database or SaaS platform
  • Access real-time synchronized data
  • Filter and search across multiple data sources
  • Retrieve specific records and datasets

Analytics & Reporting:

  • Generate custom reports from your data
  • Perform aggregations and calculations
  • Analyze trends and patterns
  • Create data visualizations

Multi-Source Queries:

  • Combine data from multiple sources
  • Cross-reference information
  • Build comprehensive dashboards
  • Track metrics across platforms

Security & Best Practices

Token Management:

Security Notice: Access tokens provide full access to your AI Connector data. Treat them like passwords.

  • Never share your access token publicly or commit it to version control
  • Regenerate tokens immediately if compromised
  • Use separate tokens for different agents or environments
  • Monitor usage in your Lemonado audit logs
  • Revoke access by regenerating the token

Access Control:

  • Configure data permissions in your Lemonado AI Connector settings
  • Use data filtering to limit what data your agents can access
  • Set up read-only access for security
  • Monitor all agent queries in real-time

Rate Limiting:

  • OpenAI enforces rate limits on API calls
  • Plan your agent's query patterns accordingly
  • Consider caching frequently accessed data
  • Monitor your Lemonado usage dashboard

Advanced Configuration

Multiple AI Connectors:

You can add multiple Lemonado AI Connectors to a single agent:

  1. Create separate AI Connectors in Lemonado for different data sources
  2. Generate a unique access token for each connector
  3. Add each as a separate MCP server in OpenAI Agent Builder
  4. Give each a descriptive name (e.g., "Lemonado-Sales", "Lemonado-Analytics")

Custom Agent Instructions:

Optimize your agent's data access by including specific instructions:

When querying Lemonado:
1. Always specify date ranges for time-series data
2. Use filters to limit result sets
3. Request only the fields you need
4. Handle empty results gracefully

Troubleshooting

Authentication Failed:

Verify token is correct:

  • Check for extra spaces or characters
  • Ensure you copied the complete token
  • Regenerate if unsure

Token expired or revoked:

  • Generate a new token in Lemonado
  • Update the token in OpenAI Agent Builder
  • Note: Tokens don't expire unless manually regenerated

Connection Issues:

  • Check MCP server URL: Ensure https://mcp.lemonado.io/mcp is entered correctly
  • Verify AI Connector status: Confirm your AI Connector is active in Lemonado
  • Test from Lemonado: Try querying your data directly in Lemonado first

No Data Returned:

  • Verify data sources are connected in your Lemonado AI Connector
  • Check data sync status - ensure recent sync was successful
  • Review permissions - confirm the AI Connector has access to required data
  • Test query syntax - verify your agent is using correct query format

Full OpenAI Agent Builder setup guide →

Install in n8n Automation

Important: Make sure you are on the latest stable version of n8n for the best compatibility with MCP.

Overview

n8n is a powerful workflow automation tool that can connect to Lemonado through the Model Context Protocol (MCP) using the MCP Client Tool node. This enables you to query and analyze your Lemonado data within automated workflows.

Prerequisites

  • n8n instance (latest version with MCP support)
  • Lemonado account with at least one data source connected
  • Active AI Connector in Lemonado

Setup Instructions

Step 1: Create an AI Connector in Lemonado

  1. Go to your Lemonado dashboard
  2. Navigate to AI Connectors
  3. Create a new AI Connector or select an existing one
  4. Choose which data sources the connector can access

Step 2: Generate Bearer Token in Lemonado

  1. In your AI Connector settings, click on the n8n tab in the left sidebar
  2. At the bottom of the page, select Expires in: 1 Year (recommended)
  3. Click Generate Token
  4. Copy the generated bearer token

Step 3: Configure n8n Workflow

  1. Open your n8n workflow editor
  2. Add an HTTP Request node or MCP node (if available)
  3. Configure the node with these settings:
    • Method: POST
    • URL: https://mcp.lemonado.io/mcp
    • Authentication: Bearer Token
  4. Add your generated bearer token to the Authorization header
  5. Test the connection and save your workflow

Step 4: Use MCP Tools

Once connected, you can use Lemonado's MCP tools:

  • execute_sql - Run SQL queries on your connected data sources
  • list_objects - List available tables and data objects
  • get_object_details - Get schema information for tables

Step 5: Build Your Workflow

Example workflow components:

  • Trigger: Schedule, webhook, or manual trigger
  • MCP Client Tool: Query Lemonado data using execute_sql
  • Process: Transform or filter the data
  • Output: Send to Slack, email, or another service

Example Workflows

Daily Sales Report:

  1. Schedule Trigger: Run daily at 9 AM
  2. MCP Client Tool: Execute SQL query 
    SELECT
  DATE(created_at) as date,
  COUNT(*) as orders,
  SUM(amount) as total_revenue
FROM orders
WHERE created_at >= CURRENT_DATE - INTERVAL '1 day'
GROUP BY DATE(created_at)
  3. Format: Convert to table or chart
  4. Email: Send report to team

Customer Data Monitoring:

  1. Schedule Trigger: Every hour
  2. MCP Client Tool: List new customers 
    SELECT * FROM customers
WHERE created_at > NOW() - INTERVAL '1 hour'
  3. IF Node: Check if new customers exist
  4. Slack: Notify sales team of new signups

Inventory Alerts:

  1. Schedule Trigger: Every 30 minutes
  2. MCP Client Tool: Check inventory levels 
    SELECT product_name, quantity, reorder_point
FROM inventory
WHERE quantity < reorder_point
  3. IF Node: Check if any items are low
  4. Create Task: Generate purchase orders

Using MCP Tools in n8n

execute_sql Tool:

  • Supports SELECT queries (read-only)
  • Returns results as JSON
  • Can query any connected data source

list_objects Tool:

  • Lists all tables and views
  • Shows data source information
  • Useful for discovery and documentation

get_object_details Tool:

  • Returns column names and types
  • Shows relationships and constraints
  • Helps with query building

Integration with AI Agents

n8n can combine MCP with AI agents:

  1. MCP Client Tool: Fetch data from Lemonado
  2. AI Agent: Analyze data with Claude, GPT, etc.
  3. Decision Node: Route based on AI analysis
  4. Action Nodes: Trigger appropriate actions

Best Practices

Performance Optimization:

  • Cache frequently accessed data
  • Use specific queries with filters
  • Implement pagination for large datasets
  • Schedule heavy queries during off-peak hours

Error Handling:

  • Add error trigger nodes to workflows
  • Implement retry logic for failed queries
  • Log errors for debugging
  • Set up alerting for critical failures

Security:

  • Use n8n's credential management
  • Enable workflow execution logging
  • Restrict access to sensitive workflows
  • Regularly review workflow permissions

Troubleshooting

Connection Issues:

  • Verify n8n is on the latest version
  • Check bearer token authentication is complete
  • Ensure AI Connector is active in Lemonado
  • Test with simple queries first

Query Errors:

  • Verify SQL syntax is correct
  • Check table and column names exist
  • Ensure you have permission to access the data
  • Use list_objects to discover available tables

Performance Issues:

  • Optimize SQL queries with indexes
  • Reduce data volume with filters
  • Use pagination for large results
  • Consider caching for repeated queries

Advanced Features

Workflow Variables:

Use n8n variables in your queries:

SELECT * FROM orders
WHERE customer_id = {{ $json.customerId }}
AND created_at > '{{ $json.startDate }}'

Dynamic Queries:

Build queries based on conditions:

const table = $json.dataSource;
const limit = $json.limit || 100;
return {
    tool: "execute_sql",
    query: `SELECT * FROM ${table} LIMIT ${limit}`,
};

Parallel Processing:

Run multiple MCP queries concurrently:

  1. Use Split In Batches node
  2. Execute MCP queries in parallel
  3. Merge results with Merge node
  4. Process combined data

Pro Tip: Use n8n's built-in variables and expressions to make your MCP queries dynamic and responsive to workflow context.

Full n8n setup guide →

View all installation guides →

Available Tools

Once connected, your AI assistant will have access to three powerful MCP tools:

  • lemonado_execute_sql - Execute SQL queries across all your connected data sources
  • lemonado_list_objects - List all available tables, views, and data sources
  • lemonado_get_object_details - Get detailed schema information for specific tables

Key Features

Query Multiple Data Sources

  • Unified Data Access: Connect and query multiple data sources through a single SQL interface

  • AI-Powered Analytics: Integrate with AI assistants like Claude, ChatGPT, and n8n for natural language data analysis

  • Real-time Integration: Access live data from platforms including Stripe, Google Ads, Meta Ads, and databases

  • Secure Authentication: OAuth 2.0 authentication and bearer token support for production deployments

Documentation

Full documentation available at: https://docs.lemonado.io/

Support

Need help? Visit data.lemonado.io or check our documentation for setup guides and troubleshooting.

Empower your AI assistant with unified SQL access to all your marketing data.

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