# Honeycomb MCP for AI Agents AI Agent Connect

> Honeycomb MCP lets you manage your observability data through an AI agent. It handles datasets, queries, and markers so you don't have to manually write complex query languages. You can inspect schemas, create timeline markers for outages, and run performance queries in plain English. It connects your Honeycomb.io account directly to your AI client.

## Overview
- **Category:** brain-trust
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_ezx3V1wqKIj03Mpp0VSR1HqDgg5PggVT54nkjF06/ai-agent-connect
- **Tags:** telemetry, high-cardinality, incident-response, data-querying, real-time-insights

## Description

This Honeycomb MCP connects your Honeycomb.io platform to your AI client, giving you a way to talk to your telemetry data instead of writing complex query languages from scratch. You can ask your agent to find specific datasets, explain what columns exist, or run queries to see why a specific service is lagging. It handles the heavy lifting of navigating high-cardinality data, letting you focus on solving the actual problem. Whether you're trying to pinpoint a deployment issue or just want to see how a new feature is performing, this integration puts your observability data in the hands of your agent. It's a huge time-saver when you're in the middle of an incident and need answers fast. You can find this in the Vinkius catalog to get started quickly. Instead of switching tabs and hunting for the right dashboard, you just tell your agent what you need to see, and it pulls the info directly from your Honeycomb account.

## Tools

### create_marker
The create_marker tool adds a timeline annotation like a deployment or maintenance window to a dataset. This helps you contextualize data spikes or planned downtime.

### get_dataset_details
The get_dataset_details tool retrieves metadata for a specific dataset. This helps you understand the core properties of your telemetry sources.

### get_team_details
The get_team_details tool retrieves information about your Honeycomb team. It provides a clear view of your organization's team configuration.

### get_query_result
The get_query_result tool retrieves the actual results of an executed query. Use it to pull the specific numbers or logs you need into your chat.

### list_dataset_columns
The list_dataset_columns tool lists all columns defined in a specific dataset. It's the fastest way to see what fields are available for querying.

### list_datasets
The list_datasets tool lists all datasets in your Honeycomb team. Use this to find the correct slugs for markers and queries.

### list_queries
The list_queries tool lists query specifications for a specific dataset. You can use this to see what queries have already been built.

### list_triggers
The list_triggers tool lists triggers defined for a dataset. It lets you see all active alerts for a specific data source.

### create_query_specification
The create_query_specification tool creates a new query for a dataset and returns a result ID. It lets your agent build complex queries from plain text instructions.

### run_query
The run_query tool executes a query specification and returns a result ID for polling. Use it to start the data retrieval process for any custom query.

### list_honeycomb_boards
The list_honeycomb_boards tool lists all boards shared with your team. This gives you a quick way to see shared dashboards across the organization.

### list_markers
The list_markers tool lists markers for a dataset. This helps you see all past annotations on a specific timeline.

## Prompt Examples

**Prompt:** 
```
Look at the 'gateway-prod' dataset and tell me what columns I can query.
```

**Response:** 
```
I've pulled the schema for 'gateway-prod'. Here are the available fields:

| Column Name | Type | Description |
| :--- | :--- | :--- |
| `request_id` | string | Unique ID for the request |
| `duration_ms` | number | Time taken to process |
| `status_code` | integer | HTTP response code |

Would you like me to run a query using any of these?
```

**Prompt:** 
```
Create a marker for a maintenance window starting now on all datasets.
```

**Response:** 
```
Done! I've added the 'Maintenance Window' marker to all your datasets. You'll see it appear on your timeline graphs in a few moments.
```

**Prompt:** 
```
Run a query for the 'main-api' dataset to find errors in the last hour.
```

**Response:** 
```
I've started that query for you. The result ID is `res_99283`. It's processing now. Should I check the results for you in a few seconds?
```

## Capabilities

### Retrieve team configuration
The get_team_details tool pulls information about your Honeycomb team configuration.

### List timeline annotations
The list_markers tool shows all the annotations on a specific dataset timeline.

### View active alerts
The list_triggers tool lists all the alerts defined for a specific dataset.

## Use Cases

### Fast Incident Response
An SRE is paged for a spike and asks the agent to run_query on the main-api dataset to find the error.

### Deployment Tracking
A developer wants to track a release and asks the agent to use list_dataset_columns to see which fields to include in a new query.

### Metadata Exploration
An engineer needs to know the properties of a specific data source and asks the agent to use get_dataset_details.

### Alert Monitoring
A platform lead needs to see all active alerts and asks the agent to list_triggers for the auth-service dataset.

## Benefits

- Stop fighting with complex query syntax by letting your agent handle the logic for you with create_query_specification.
- Get faster incident response by using create_marker to tag deployments or outages on your timeline instantly.
- Keep your team organized by using list_honeycomb_boards to see shared dashboards without leaving your chat.
- Understand your data structure quickly with list_queries to see what's already been built for your datasets.
- Speed up troubleshooting with get_query_result to pull performance insights directly into your conversation.

## How It Works

The bottom line is you get to talk to your telemetry data using natural language instead of manual DSL entry.

1. Subscribe to the Connector on Vinkius.
2. Enter your Honeycomb API Key and select your region.
3. Ask your agent to run a query or create a marker.

## Frequently Asked Questions

**Can the Honeycomb MCP help me during an outage?**
Yes, it lets you query telemetry data instantly using natural language. This helps you find the root cause of issues much faster than manual querying.

**How do I use Honeycomb MCP to see my datasets?**
You can simply ask your agent to list all the datasets in your team. It will pull the list of available sources directly from your account.

**Does Honeycomb MCP support creating markers?**
Yes, it handles markers for things like deployments, outages, and maintenance windows. This helps you add context to your timeline data automatically.

**Can I see my team's boards with Honeycomb MCP?**
Yes, it can list all the boards shared with your team. This gives you a quick way to see your team's dashboards without leaving your current workspace.

**What's the benefit of Honeycomb MCP for SREs?**
It helps you get answers faster during a crisis. Instead of writing complex DSLs, you can just ask your agent to find the data you need.

**How do I get query results from Honeycomb MCP?**
The agent runs the query for you and then pulls the results directly into the chat. You don't have to switch tabs to see the data.

**How do I find my Honeycomb API Key?**
Log in to Honeycomb, go to **Team Settings**, and navigate to the **API Keys** section. You will be able to generate and copy your Team API Key from there. Ensure you also note your account's region.

**Which region should I select?**
If your browser URL starts with `ui.eu1.honeycomb.io`, select **EU**. Otherwise, select **US**. Using the correct region is required for the integration to connect to the right API cluster.

**Can I run a query and get the data back?**
Yes! Use the `run_query` tool with a valid query ID. It will return a result ID, which you can then pass to the `get_query_result` tool once the analysis is complete.

**Is the integration secure for telemetry data?**
Absolutely. The integration uses official Honeycomb Team API keys over HTTPS. Your credentials and queried data are encrypted and stored securely within the Vinkius Cloud infrastructure.