> ## Documentation Index
> Fetch the complete documentation index at: https://docs.veecle.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

> Connect your AI coding agent to Chiplab and run your first firmware simulation.

This guide walks you from a brand-new Chiplab account to a completed firmware simulation.
By the end, your AI coding agent will be connected to Chiplab and you'll have seen real UART output from a virtual chip instance, no physical hardware required.

<Steps>
  <Step title="Sign in to Chiplab">
    Go to [chiplab.veecle.ai](https://chiplab.veecle.ai) and sign in with your account.
    It's self-serve: no credit card needed, and there's a free tier to get you started.
  </Step>

  <Step title="Connect your agent">
    Navigate to **API Keys** in the sidebar, then click **Connect agent**.
    Select your agent from the list, Cursor, OpenCode, Claude Code, and others, and follow the instructions on screen.

    Each agent needs a short configuration step to register the Chiplab MCP server (`https://chiplab.veecle.ai/mcp`), followed by a browser-based authentication step.
    The dashboard shows the exact commands and config snippets for your chosen agent, or see the per-agent guides below.

    If you're working from a clone of this repo, some agents are pre-configured: Claude Code picks up [`.mcp.json`](https://github.com/veecle/chiplab/blob/main/.mcp.json) automatically and just prompts you to trust it.
    Otherwise, add Chiplab like any other MCP server; see [Connect your agent](#connect-your-agent) below for the exact config for your client.
    On first use your client opens a browser to sign in.
  </Step>

  <Step title="Build and run an example">
    With your agent connected, verify the connection by asking it to call Chiplab's `ask` tool with no arguments; it should come back with a platform overview.

    Then try a real simulation. Clone this repo:

    ```sh theme={null}
    git clone https://github.com/veecle/chiplab && cd chiplab
    ```

    Then just tell your agent:

    ```text theme={null}
    Build and run examples/bare-metal/stm32f4-discovery on Chiplab.
    ```

    Your agent installs what's needed, builds the binary, uploads the ELF, and runs it on a virtual STM32F4 Discovery board.
    The run returns synchronously, bounded to a fixed amount of virtual time, and you'll see `Hello world!` in the captured UART output.

    This same produce-an-ELF → upload → run → read-output flow works for every board and framework this repo ships examples for; only the ELF path and board change.
    See [supported-boards.md](https://github.com/veecle/chiplab/blob/main/supported-boards.md) for the full board list.
  </Step>

  <Step title="Ask questions about Chiplab">
    Your agent can also query Chiplab directly; you don't need to prompt this explicitly.
    It happens automatically whenever your agent needs context, most commonly the first time it uses Chiplab in a session.
  </Step>
</Steps>

## Connect your agent

<CardGroup cols={2}>
  <Card title="Connect Cursor" icon="arrow-pointer" href="/agents/cursor">Configure Chiplab in Cursor's MCP settings and authenticate.</Card>
  <Card title="Connect OpenCode" icon="terminal" href="/agents/opencode">Register Chiplab in your OpenCode config and run the auth command.</Card>
  <Card title="Connect Claude Code" icon="comment-code" href="/agents/claude-code">Add Chiplab via the Claude CLI and authenticate with `/mcp`.</Card>
  <Card title="Other agents" icon="ellipsis" href="/agents/overview">Claude Desktop, VS Code, Codex, and any other MCP-capable client.</Card>
</CardGroup>