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ToeBox agents can use tools to interact with external systems, query data, and take actions on behalf of your customers. Tools are connected via the Model Context Protocol (MCP).

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MCP tool connections

MCP (Model Context Protocol) tools connect your agents to live data and actions. ToeBox includes built-in connections to Shopify’s official MCP servers:

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Shopify Catalog

Lets your agent search and browse products across your Shopify store. Capabilities:
  • Search products by keyword, category, or attribute
  • Retrieve product details (title, description, price, images, variants)
  • Filter by price range and availability
  • Browse collections
Endpoint: https://discover.shopifyapps.com/global/mcp

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Shopify Checkout

Lets your agent create checkout sessions and guide customers through purchases. Capabilities:
  • Create checkout sessions
  • Collect buyer information
  • Attach payment methods
  • Complete purchases
Endpoint: https://{shop-domain}/api/ucp/mcp
MCP tools are auto-configured based on your agent type. For example, a Product Recommendation agent automatically enables the Catalog tool, while a Sales Assistant enables both Catalog and Checkout.

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Data tools

When you connect data sources (Snowflake, PostgreSQL, or other databases), your agents gain access to built-in data tools:
ToolDescription
list_tablesLists all tables in the connected database
describe_tableReturns column names, types, and metadata for a specific table
query_databaseExecutes a read-only SQL query and returns results
These tools let agents answer data-driven questions like “What were our top-selling products last month?” by querying your data warehouse directly.
Data tools execute read-only queries. Write operations (INSERT, UPDATE, DELETE) are blocked at the connector level for safety.

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Custom SQL tools

You can create custom SQL tools that wrap a specific query behind a friendly name and description. This is useful for:
  • Giving agents access to a frequently-used report
  • Restricting what data an agent can access
  • Pre-building complex queries so the agent does not need to generate SQL
To create a custom SQL tool:
  1. Go to your agent’s configuration
  2. Open the Custom Tools section
  3. Click Add Tool
  4. Provide a name, description, and SQL query
  5. The agent can then call this tool by name during conversations

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Custom tool builder

For advanced use cases, the custom tool builder lets you define tools with:
  • Name — What the agent calls this tool
  • Description — Helps the AI understand when to use the tool
  • Parameters — Input parameters the tool accepts (with types and descriptions)
  • SQL query — The query to execute, with parameter placeholders
Write clear tool descriptions. The AI model uses the description to decide when to call a tool, so be specific about what it does and when it should be used.