> **Building with AI coding agents?** If you're using an AI coding agent, install the official Scalekit plugin. It gives your agent full awareness of the Scalekit API — reducing hallucinations and enabling faster, more accurate code generation.
>
> - **Claude Code**: `/plugin marketplace add scalekit-inc/claude-code-authstack` then `/plugin install <auth-type>@scalekit-auth-stack`
> - **GitHub Copilot CLI**: `copilot plugin marketplace add scalekit-inc/github-copilot-authstack` then `copilot plugin install <auth-type>@scalekit-auth-stack`
> - **Codex**: run the bash installer, restart, then open Plugin Directory and enable `<auth-type>`
> - **Skills CLI** (Windsurf, Cline, 40+ agents): `npx skills add scalekit-inc/skills --list` then `--skill <skill-name>`
>
> `<auth-type>` / `<skill-name>`: `agentkit`, `full-stack-auth`, `mcp-auth`, `modular-sso`, `modular-scim` — [Full setup guide](https://docs.scalekit.com/dev-kit/build-with-ai/)

---

# Overview

AgentKit gives your AI agents authenticated access to third-party apps: sending emails, reading calendars, creating tickets, querying databases, and more. Your agent calls a tool; Scalekit handles the OAuth flow, token storage, and API call.

## Authentication

**Connections** are configurations you create once in the Scalekit Dashboard. A connection holds the credentials Scalekit needs to authenticate with a connector (OAuth app credentials, API keys, or service account details). One connection serves all your users.

**Connected accounts** are per-user instances of a connection. When a user authorizes, Scalekit creates a connected account that stores their tokens and tracks their auth state. Your agent uses a connected account to act on that specific user's behalf.

Scalekit supports OAuth 2.0, API keys, RSA key pairs, and service accounts across all connectors.

## Tool calling

**Connectors** are the pre-built integrations your agent can use: Gmail, Slack, Salesforce, Snowflake, GitHub, and many others. Each connector exposes a library of tools ready for your agent to call.

**Tools** are connector-specific actions: `gmail_fetch_emails`, `salesforce_create_record`, `slack_send_message`. Scalekit provides the tool schemas and handles the authenticated API call. Your agent passes inputs; Scalekit injects the user's credentials and returns structured output.

## How they fit together

```d2
direction: right

Dev: "You (developer)"
Users: "Your users"
Agent: "Your agent"

Scalekit: {
  Conn: "Connection\n(credentials + config)"
  CA: "Connected accounts\n(per-user auth state)"
  Tools: "Tools\n(pre-built + proxied)"
}

Provider: "Third-party app\n(Gmail, Slack, Snowflake…)"

Dev -> Scalekit.Conn: "Configure once"
Users -> Scalekit.CA: "Authenticate"
Agent -> Scalekit.Tools: "Call tools"
Scalekit.Tools -> Provider: "Authenticated API call"
```

You configure connections once. Your users authenticate to create connected accounts. Your agent calls tools; Scalekit handles the rest.

## Works with your framework

AgentKit is framework-agnostic. Tool schemas work with any LLM API. Native adapters are available for [LangChain](/agentkit/examples/langchain/), [Google ADK](/agentkit/examples/google-adk/), and [MCP-compatible environments](/agentkit/mcp/configure-mcp-server/).

## Get started

[Quickstart](/agentkit/quickstart)
  [Configure a connection](/agentkit/connections)
  [Connectors](/agentkit/connectors/)
  [Examples](/agentkit/examples/)

---

## More Scalekit documentation

| Resource | What it contains | When to use it |
|----------|-----------------|----------------|
| [/llms.txt](/llms.txt) | Structured index with routing hints per product area | Start here — find which documentation set covers your topic before loading full content |
| [/llms-full.txt](/llms-full.txt) | Complete documentation for all Scalekit products in one file | Use when you need exhaustive context across multiple products or when the topic spans several areas |
| [sitemap-0.xml](https://docs.scalekit.com/sitemap-0.xml) | Full URL list of every documentation page | Use to discover specific page URLs you can fetch for targeted, page-level answers |