Skip to content
/
AI best practices
Last updated

Using AI tools with Fax API

Note:

This guide includes best practices for using generative AI tools with Sinch's Fax API. Generative AI can make mistakes, and Sinch has limited influence over the output of any given generative AI tool. Ensure you review any code produced by generative AI to confirm its accuracy, stability, and security against our documentation, your environment, and your needs.

You can use AI tools to facilitate the generation of code that you can use with Sinch's Fax API.

While there are any number of ways to make use of AI tools, we provide guidance on using Sinch's documentation MCP server to utilize our documentation.

Using Sinch's documentation MCP server

In order to generate code samples using AI tools, you may connect directly to Sinch's documentation MCP server. This will make several tools available to your system that facilitate endpoint identification, information lookups, and general context-setting.

Note:

Sinch's documentation MCP server provides tools that help you navigate Sinch's documentation. Because Sinch's documentation includes various code samples, it can also help you generate code samples. It will not make calls to the identified endpoints for you; you must include any provided code in your solution and customize it to correctly reference your account and credentials.

The tools are described in the table below. Note that, while you may not have to explicitly call out these tools when designing your prompt (or using the prompts we provide later in this document), you must still ensure the tools are activated in whatever AI environment you work in:

ToolParametersDescription
whoamiNoneReturns information about the authenticated user.
list-apisname?: stringLists available APIs with their context and purpose.
get-endpointsname: stringReturns all endpoints and their descriptions for a specific API.
get-endpoint-infoname: string``path: string``method: stringReturns comprehensive information about a specific endpoint, including parameters, security, and examples.
get-security-schemesname: string``path: string``method: stringGets the security schemes for a specific API.
get-full-api-descriptionname: stringReturns the complete OpenAPI description.
searchquery: stringSearches documentation and returns relevant content for a query.

Connecting to the MCP server

You may connect to our documentation MCP server by clicking the Connect MCP button:

Note:

The AI tools listed in the Connect MCP button drop-down list and the tools described below are for illustrative purposes. You may use our documentation MCP server with any AI tool that can connect to MCP servers.

Alternatively, copy the following URL and add it to your AI tool: https://developers.sinch.com/mcp. Some examples of how to add the Sinch documentation MCP server tools to your AI solution are detailed in the tabs below:

Connect Cursor to the MCP server

  1. In Cursor, open the command palette.
  • macOS: Command + Shift + P
  • Windows/Linux: Ctrl + Shift + P
  1. Type "Open MCP settings" in the command palette.
  2. Select "Add custom MCP".

Cursor opens the mcp.json file.

Configure the MCP server

  1. In mcp.json, add your server configuration:
{
  "mcpServers": {
    "sinch-mcp": {
      "url": "https://developers.sinch.com/mcp"
    }
  }
}
  1. Save the mcp.json file.
  2. Return to MCP settings and confirm the connection.

If authentication is required, select Needs login and complete the sign-in flow. After connecting, Cursor displays the list of available tools.

Test the Cursor connection

In Cursor chat (Agent mode), ask a question that triggers an MCP tool.

Previous page
Next page