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

# Honeycomb MCP Prompts Reference

> Reference for the prompts Honeycomb MCP provides to AI agents, including guided onboarding, workspace tours, and OpenTelemetry help

## Overview

Run a Honeycomb MCP prompt to start a guided, multi-step workflow in your AI agent without writing the instructions yourself.

A prompt is a set of pre-written instructions that your agent follows, often by calling several [MCP tools](/integrations/mcp/tools/) in sequence.
Your agent chooses tools on its own based on what you ask, while you run a prompt when you want a specific workflow.

## Syntax

AI agents typically display MCP prompts as slash commands, such as `/honeycomb-onboarding`.
The exact name can vary by agent.
For example, Cursor displays `/honeycomb-onboarding` as `/honeycomb/honeycomb-onboarding`.

<Note>
  Honeycomb MCP prompts differ from commands in the [Honeycomb plugin](/integrations/agent-skills/), such as `/honeycomb-setup`.
  Plugin commands exist only when you install the plugin.
  MCP prompts come from the Honeycomb MCP server, so they work with or without the plugin.
</Note>

## Before you begin

Prompts run through your Honeycomb MCP connection, so set up that connection first.
Make sure that:

* Your AI agent connects to Honeycomb MCP and authenticates.
  To set up a connection, visit [Connect to Honeycomb MCP](/integrations/mcp/configuration-guide/).
* Your AI agent supports MCP prompts.

Prompts don't require any additional scopes.

## Onboarding and learning prompts

These prompts help new users get data into Honeycomb and learn how to work with it.

<ParamField path="honeycomb-onboarding">
  Guides you through getting data into Honeycomb.
  Your agent asks which path you want to follow:

  * **Get real data into Honeycomb:** Send telemetry from your app.
  * **Send sample data:** Generate sample data based on your codebase.
  * **Analyze existing data:** Explore data already in your environment.

  On the real data path, your agent reviews your repository and chooses a next step based on what it finds:

  * **Already sending to Honeycomb:** Your agent confirms that your events arrive.
  * **Sending OpenTelemetry data somewhere else:** Your agent points your existing exporter at Honeycomb.
  * **Sending data to Datadog or New Relic:** Your agent adds an OpenTelemetry Collector alongside your existing agent, so Honeycomb receives a copy of your data while your current vendor keeps receiving it.
    If you prefer, your agent can replace your vendor instrumentation with OpenTelemetry instead.
  * **Little or no instrumentation:** Your agent offers to add OpenTelemetry to your app.
    With the [Honeycomb plugin](/integrations/agent-skills/) installed, your agent instruments your app for you.
    Without the plugin, your agent guides you through instrumenting your app manually.

  Once your first events arrive, your agent helps you start a [Canvas](/investigate/canvas/) investigation.
</ParamField>

<ParamField path="honeycomb-learning">
  Gives you a guided tour of your Honeycomb workspace.
  This prompt doesn't instrument your app or send data.
  Your agent asks which path you want to follow:

  * **Exploring:** Environments, datasets, columns, queries, SLOs, and Triggers.
  * **Debugging:** Heatmaps, traces, and BubbleUp.
  * **Reliability:** SLOs and error budgets.
</ParamField>

## OpenTelemetry instrumentation prompts

These prompts help your agent evaluate and improve the OpenTelemetry instrumentation in your code.
Each prompt accepts either a code snippet or a path to a code file.
When you provide a file path, your agent reads the file itself, so it needs access to that file.

<ParamField path="otel_analysis">
  Asks your agent to explain your code and suggest OpenTelemetry automatic instrumentation, with links to the OpenTelemetry documentation for your language.
  This prompt produces guidance and doesn't change your code.

  **Arguments:** Provide either `code_snippet` (the code as text) or `file_path` (the path to a code file).
</ParamField>

<ParamField path="otel_custom_instrumentation">
  Asks your agent to add custom OpenTelemetry spans to your code.

  **Arguments:** Provide either `code_snippet` (the code as text) or `file_path` (the path to a code file).
</ParamField>

## Troubleshooting

Running into issues? Here are some common problems and ways to fix them.

<Tip>
  Still stuck?
  Visit the [Support Knowledge Base](/troubleshoot/customer-support/) or post a question in the [Pollinators Community](/troubleshoot/community/).
</Tip>

### Prompts don't appear in your agent

When Honeycomb MCP tools work but a prompt like `/honeycomb-onboarding` doesn't appear, the cause is usually how your agent names or loads prompts.
Check the following:

* **Look for a different name:** Some agents add a prefix to prompt names.
  For example, Cursor displays `/honeycomb-onboarding` as `/honeycomb/honeycomb-onboarding`.
* **Confirm your agent supports MCP prompts:** Agents that support only MCP tools don't display prompts.
* **Check your toolset header:** If you configured the `X-MCP-Toolset` header, set it to `all` or `query`, or remove it.
  A value of `canvas` doesn't include prompts.
  To learn more, visit [Connect to Honeycomb MCP: Limit the tools your agent loads](/integrations/mcp/configuration-guide#limit-the-tools-your-agent-loads).

## Next steps

* [Connect to Honeycomb MCP](/integrations/mcp/configuration-guide/): Set up your AI agent so it can run prompts.
* [MCP Tools Reference](/integrations/mcp/tools/): Review the tools prompts call on your behalf.
* [Agent Skills](/integrations/agent-skills/): Install the plugin for automatic instrumentation during onboarding.
* [Try Honeycomb with data from Datadog or New Relic](/integrations/mcp/use-cases#trying-honeycomb-with-data-from-datadog-or-new-relic): Send data to Honeycomb while keeping your existing vendor setup in place.