Skip to main content
Quickstart:
  1. Use Nango’s documentation MCP: https://nango.dev/docs/mcp
  2. Install the function builder skill: npx skills add NangoHQ/skills

​
Overview

Nango’s AI builder generates and assists in implementing Functions using the IDE and model of your choice. It feeds the necessary context to the model, Nango’s interface, best coding practices, and testing patterns, so you can describe your use case and get production-ready code with minimal manual effort. Unlike black-box integrations, Nango generates human-readable code that you can review, edit, and maintain. The AI builder also generates mock-based tests for your CI/CD pipeline, and follows battle-tested patterns from hundreds of production integrations.

​
Supported agents

Nango’s function builder is distributed as a Vercel skill and works with 18+ AI frameworks including Claude Code, Cursor, GitHub Copilot, Gemini CLI, Codex, OpenCode, and more.

​
Install the Nango function builder skill

Install Nango’s skill pack into your development environment: 
npx skills add NangoHQ/skills
This adds nango-function-builder, which includes guidance for building both Actions and Syncs.
If your coding agent is already running, restart it after installing the skill so it can load the new instructions.

​
Use it with your coding agent

The nango-function-builder skill is loaded automatically when using popular coding agents/tools (Claude Code, Cursor, Gemini CLI, Codex CLI, VS Code with Copilot, Opencode, and more). Tell your agent what you want to build. You can start with a simple prompt to build an Action: 
I want to build a Nango action that will get specified Slack channel information.
However, the more information you give the agent up-front, the better the initial version of the Action is going to be: 
I want to build a Nango action that will get Slack channel information.

Integration ID: slack
Connection ID: my-slack-connection
Inputs: channel_id
Outputs: id, name, is_private
API Reference: https://api.slack.com/methods/conversations.info
Similarly, a prompt to build a Sync could look like this: 
I want to build a Nango sync that will store all Figma projects.

Integration ID: figma
Connection ID: my-figma-connection
Frequency: every hour
Inputs: team_id
Outputs: Project model with fields id, name, last_modified
API Reference: https://www.figma.com/developers/api#projects-endpoints

​
What the agent does

Once you provide your input, your agent typically:
  1. Generates the function code - Creates a complete action or sync implementation
  2. Creates a full test suite - Writes comprehensive tests
  3. Validates with dry run - Runs nango dryrun to verify against your connection
  4. Iterates on failures - Automatically debugs and fixes issues
You’ll end up with a fully tested, working function ready to deploy.
The more detail you provide, the better the generated function will be. Include API documentation links when available.