AI

Build with Kustomer AI and build Kustomer integrations with AI. The AI and automations API, the kusty CLI and MCP server for coding agents, and docs published in formats models can read.

There are two sides to AI on this site: APIs for working with Kustomer AI (summaries, AI agents and their evaluations), and tools that let your AI assistants work with Kustomer (the kusty MCP server and machine-readable docs).

AI and automations API

Read AI summaries, list your AI agents, and test them with evaluations from scripts and CI.

kusty CLI

The whole Kustomer API from the command line, with JSON output and exit codes built for agents.

kusty MCP server

Give Claude Code, Cursor, Codex or Gemini CLI typed tools for every Kustomer endpoint.

Docs for AI

llms.txt, Markdown for every page and operation, and a docs MCP server to feed your models.

Which tool for which job

You want toUse
Show AI summaries of conversations in your CRM, BI tool or SlackSummaries API
Catch regressions in an AI agent before you turn on a changeEvaluations API, run from CI
Ask your coding assistant "which customers wrote in about order 4417?"kusty MCP server
Script one-off data fixes and exports with JSON you can pipe to jqkusty CLI
Have an assistant write integration code against KustomerDocs for AI: point it at llms.txt or a page's .md

Building AI features on Kustomer events

The rest of the platform works well with your own models too:

  • Webhooks stream conversation and message events to your service as they happen.
  • Workflows can call your AI service with a REST action and write the answer back to a conversation.
  • The server-side chat API lets your own bot answer chats, with an AI typing indicator.
  • Apps package all of this so other orgs can install it.