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

# Chronosphere MCP server

> Learn how to connect large language models to the Chronosphere MCP server.

Connect large language models (LLMs) to Chronosphere Observability Platform using
the Model Context Protocol (MCP) server. After connecting, your LLM can:

* Query [telemetry data](/overview/types) including change events, metrics, logs, and
  traces.
* Read [Chronosphere resources](/integrate/mcp-server/resources), such as dashboards
  and monitors.
* Search and retrieve Chronosphere documentation through the
  [documentation MCP server](https://docs.chronosphere.io/mcp).

<Note>
  The Chronosphere MCP server is read-only. It doesn't support mutation actions such
  as updating dashboards, writing metrics and logs, or deleting monitors.
</Note>

Use AI-enabled developer tools such as [Claude Code](https://www.claude.com/product/claude-code),
[Cursor](https://cursor.com/home?from=agents),
[Codex](https://developers.openai.com/codex/mcp/),
and [Gemini](https://github.com/google-gemini/gemini-cli/tree/main) to submit queries.
Example use cases:

* Find error logs with stack traces and review code for root cause analysis.
* Fetch a monitor's configuration and explain what's triggering it.
* Write PromQL queries targeting a specific service's metrics.
* List active shaping rules, such as drop rules, to determine why data is or isn't
  being dropped.

## Get started

To get started with the Chronosphere MCP server,
[configure authentication](/integrate/mcp-server/authenticate).