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

# AI Overview

> Connect AI agents and MCP clients to Bronto, run AI-driven investigations, and turn raw telemetry into structured, queryable observability data.

Bronto gives you multiple ways to bring AI into your observability workflows.

Whether you want to connect an MCP client, run the server locally, investigate production issues with AI, or automatically structure raw telemetry, this section will help you get started.

<CardGroup cols={2}>
  <Card title="Hosted MCP" icon="cloud" href="/ai-features/hosted-mcp">
    Connect Claude or another MCP-compatible client directly to Bronto’s hosted endpoint. No local server required.
  </Card>

  <Card title="Local MCP" icon="terminal" href="/ai-features/local-mcp">
    Run the Bronto MCP server on your own machine with Python and connect it to Claude Code or another compatible agent.
  </Card>

  <Card title="BrontoScope" icon="sparkles" href="/ai-features/brontoscope">
    Automatically investigate events and issues with AI and get scope, likely causes, next steps, and supporting evidence in seconds.
  </Card>

  <Card title="AI Investigation Reports" icon="file-lines" href="/ai-features/ai-investigation-reports">
    Attach AI-generated investigation reports to monitor alerts using a prompt that tells Bronto what to check.
  </Card>

  <Card title="Custom Parser" icon="wand-sparkles" href="/core-features/custom-parser">
    Use AI to turn unstructured telemetry into structured, queryable events with custom parsers tailored to your data.
  </Card>

  <Card title="Vibe Building" icon="bolt" href="/ai-features/vibe-building">
    Build custom observability interfaces with tools like Lovable and v0 on top of Bronto APIs.
  </Card>
</CardGroup>

## What you can do

<CardGroup cols={2}>
  <Card title="Connect AI to your data">
    Give agents access to datasets, keys, field values, search, and aggregated analysis workflows through MCP.
  </Card>

  <Card title="Investigate incidents faster">
    Use BrontoScope to automatically assess impact, identify likely causes, and surface recommended next steps.
  </Card>

  <Card title="Enrich monitor alerts">
    Add AI Investigation Reports to monitors so alerts arrive with automated analysis and recommended follow-up.
  </Card>

  <Card title="Reduce setup friction">
    Start quickly with Hosted MCP, or choose Local MCP when you need more control over how the server runs.
  </Card>

  <Card title="Make unstructured data usable">
    Create custom parsers that extract fields from application, system, and custom data formats so your data is easier to search and analyze.
  </Card>

  <Card title="Build focused custom UIs">
    Use Bronto APIs to create workflow-specific dashboards, service maps, and operational views.
  </Card>
</CardGroup>

## Recommended workflows

### 1. Connect an agent to Bronto

Start with one of the MCP options:

* Choose **Hosted MCP** for the simplest setup
* Choose **Local MCP** if you want to run the server yourself

<CardGroup cols={2}>
  <Card title="Hosted MCP" href="/ai-features/hosted-mcp" icon="cloud">
    Managed by Bronto. Best for the fastest path to an MCP connection.
  </Card>

  <Card title="Local MCP" href="/ai-features/local-mcp" icon="terminal">
    Runs locally with Python. Best when you need control or a self-managed setup.
  </Card>
</CardGroup>

### 2. Investigate a production issue

When you hit an unfamiliar issue, use BrontoScope to get an immediate starting point for your investigation.

<Card title="Investigate with BrontoScope" href="/ai-features/brontoscope" icon="sparkles">
  Ideal for quickly understanding impact, likely causes, and the next queries to run.
</Card>

### 3. Add AI analysis to monitor alerts

If you want investigations to run automatically when alerts fire, configure AI Investigation Reports on the monitor itself.

<Card title="AI Investigation Reports" href="/ai-features/ai-investigation-reports" icon="file-lines">
  Best for monitor-driven workflows where responders need a diagnosis attached to the alert.
</Card>

### 4. Improve the quality of your data

If your data is hard to search because it is unstructured, create a parser first.

<Card title="Structure data with Custom Parser" href="/core-features/custom-parser" icon="wand-sparkles">
  Transform raw telemetry into structured fields that are easier to search, group, and analyze.
</Card>