Hosted MCP
Connect Claude or another MCP-compatible client directly to Bronto’s hosted endpoint. No local server required.
Local MCP
Run the Bronto MCP server on your own machine with Python and connect it to Claude Code or another compatible agent.
BrontoScope
Automatically investigate events and issues with AI and get scope, likely causes, next steps, and supporting evidence in seconds.
AI Investigation Reports
Attach AI-generated investigation reports to monitor alerts using a prompt that tells Bronto what to check.
LLM Observability
Capture prompts, responses, token usage, and model metadata from your own LLM-powered applications using the OpenTelemetry GenAI semantic conventions, and search them in Bronto.
Custom Parser
Use AI to turn unstructured telemetry into structured, queryable events with custom parsers tailored to your data.
Vibe Building
Build custom observability interfaces with tools like Lovable and v0 on top of Bronto APIs.
What you can do
Connect AI to your data
Give agents access to datasets, keys, field values, search, and aggregated analysis workflows through MCP.
Investigate incidents faster
Use BrontoScope to automatically assess impact, identify likely causes, and surface recommended next steps.
Enrich monitor alerts
Add AI Investigation Reports to monitors so alerts arrive with automated analysis and recommended follow-up.
Reduce setup friction
Start quickly with Hosted MCP, or choose Local MCP when you need more control over how the server runs.
Observe your own LLM apps
Instrument applications that call OpenAI, Anthropic, Amazon Bedrock, or LangChain with the OpenTelemetry GenAI semantic conventions and send that telemetry to Bronto.
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.
Build focused custom UIs
Use Bronto APIs to create workflow-specific dashboards, service maps, and operational views.
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
Hosted MCP
Managed by Bronto. Best for the fastest path to an MCP connection.
Local MCP
Runs locally with Python. Best when you need control or a self-managed setup.
2. Investigate a production issue
When you hit an unfamiliar issue, use BrontoScope to get an immediate starting point for your investigation.Investigate with BrontoScope
Ideal for quickly understanding impact, likely causes, and the next queries to run.
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.AI Investigation Reports
Best for monitor-driven workflows where responders need a diagnosis attached to the alert.
4. Improve the quality of your data
If your data is hard to search because it is unstructured, create a parser first.Structure data with Custom Parser
Transform raw telemetry into structured fields that are easier to search, group, and analyze.
5. Instrument an LLM-powered application
If your own application calls an LLM — directly, via Amazon Bedrock/AgentCore, or through LangChain — capture that as GenAI telemetry rather than plain logs.LLM Observability
Best for teams shipping LLM or agent features who want prompts, responses, token usage, and model metadata searchable in Bronto.