Fresha

MCP (Model Context Protocol) server for accessing Fresha Data Connector via Snowflake. Query your Fresha business data directly through AI assistants like Claude.

Add to~/Library/Application Support/Claude/claude_desktop_config.json:

{ "mcpServers": { "fresha": { "command": "mcp-fresha", "env": { "SNOWFLAKE_ACCOUNT": "your-account.snowflakecomputing.com", "SNOWFLAKE_USER": "FRESHA_DATA_XXX_XXX", "SNOWFLAKE_PASSWORD": "your-password", "SNOWFLAKE_DATABASE": "FRESHA_DATA_CONNECTOR", "SNOWFLAKE_SCHEMA": "FRESHA_DATA_XXX", "SNOWFLAKE_WAREHOUSE": "FRESHA_DATA_XXX" } } } }

Important: If your password contains#, wrap it in quotes:"password#123"

Get these credentials from your Fresha Data Connector settings.

- Real-time Data Access: Direct connection to your Fresha business data through Snowflake
- Flexible Querying: Support for date ranges, custom filters, sorting, and pagination
- Smart Date Parsing: Natural language date inputs like "yesterday", "last week", "this month"
- Comprehensive Schema Discovery: Automatic discovery of all available tables and their structures
- Type-safe Operations: Built with TypeScript for reliability and maintainability
- Mock Mode: Development mode with sample data when Snowflake credentials are not available
- Structured Logging: Detailed logging with Pino for debugging and monitoring

Lists all available tables and views in your Fresha database.

Example: "Show me all tables"

Get data from any Fresha report/table with flexible filtering options.

- report_name(required) - Name of the table (e.g., CASH_FLOW, SALES, BOOKINGS)
- start_date(optional) - Start date filter (YYYY-MM-DD)
- end_date(optional) - End date filter (YYYY-MM-DD)
- limit(optional) - Max records to return (default: 1000)
- order_by(optional) - Column to sort by (e.g., "SALE_DATE DESC")
- filters(optional) - Additional filters as key-value pairs

- "Get yesterday's cash flow"
- "Show me top 10 clients by appointment count"
- "Get all bookings for this week"
- "Show sales from location 123"

- CASH_FLOW- Transaction-level cash flow data
- BOOKINGS- Service bookings and appointments
- CLIENTS- Client information and history
- PAYMENTS- Payment transactions
- SALES- Sales records
- LOCATIONS- Business locations
- TEAM_MEMBERS- Staff information
- And more...

- Ensure credentials match exactly from Fresha Data Connector
- Check for special characters in password (especially#)
- Removehttps://from account URL if present

- Verify you have the correct database and schema names
- Check Fresha Data Connector is active (8-hour daily limit)

- Environment Variables: All sensitive credentials are stored as environment variables, never in code
- No Credential Logging: The server automatically masks Snowflake credentials in logs
- Read-Only Access: Designed for read-only operations to prevent accidental data modifications
- Input Validation: All tool inputs are validated using Zod schemas to prevent injection attacks
- Parameterized Queries: All database queries use parameterized statements to prevent SQL injection
- Session Management: Each connection is properly managed with automatic cleanup

- Credentials are never exposed in error messages or logs
- Mock mode prevents accidental production data access during development
- All database connections are encrypted using Snowflake's secure protocols

# Clone and install git clone https://github.com/199-biotechnologies/mcp-fresha.git cd mcp-fresha/fresha-mcp-server npm install # Configure environment cp .env.example .env # Edit .env with your credentials # Build and test npm run build npm test # Development mode with mock data npm run dev # Watch mode for development npm run watch # Lint and type check npm run lint npm run typecheck

The project follows a clean architecture pattern:

- Controllers: Business logic for handling data queries and transformations
- Services: Data access layer with Snowflake connection management
- Tools: MCP tool definitions that expose functionality to AI assistants
- Utils: Shared utilities for logging, date parsing, and error handling

Contributions are welcome! Please ensure:

- All code passes linting (npm run lint)
- TypeScript types are properly defined
- New features include appropriate error handling
- Security best practices are followed

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