# Honeycomb — MCP Server

> Query high-cardinality traces and let an agent chase the outlier, not the average.

**Source:** https://mcpplaygroundonline.com/mcp-servers/honeycomb  
**Transport:** http  
**Requires auth:** Yes

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## What it does

The server exposes Honeycomb’s query surface over your datasets. An agent can list datasets and their columns to discover what dimensions exist, then compose a query with breakdowns, calculations, filters and orders — the same primitives as the query builder. That discovery step matters more here than in most observability tools, because Honeycomb’s value is in dimensions nobody thought to put on a dashboard, and a model that can enumerate columns will find them. Traces are retrievable for following a single slow request through services, and SLO and burn-alert state is readable so an agent can tie a spike to whether it is actually eating error budget. The workflow it enables is iterative: query, notice an outlier, break down by another dimension, repeat — which is exactly the loop that costs a human twenty minutes.

## Tools exposed

- list datasets — enumerate datasets and the columns available on each
- run query — breakdowns, calculations, filters and time ranges over a dataset
- traces — fetch a trace and walk its spans
- SLOs — read service level objectives and burn-alert state
- triggers — read alerting triggers and their current status

## Example queries you can run

- "Which customer IDs are seeing p99 latency above two seconds on the API dataset?"
- "Break down errors in the last hour by endpoint and then by build ID."
- "Fetch the slowest trace from the last thirty minutes and explain where the time went."
- "Are any SLOs burning error budget faster than usual today?"

## Details

- **Recommended model:** anthropic/claude-sonnet-4.5 — Useful Honeycomb work is iterative refinement across several queries. Sonnet 4.5 keeps the earlier results in mind and narrows; cheaper models restart the investigation each turn.
- **Transport:** http
- **Authentication:** Required — A Honeycomb API key scoped to the environment you want readable. Keys are per-environment, so production and staging need separate ones.
- **Hosted endpoint:** https://mcp.honeycomb.io/mcp
- **Official source:** [Honeycomb documentation](https://docs.honeycomb.io/)

## Frequently asked questions

### What is the Honeycomb MCP server?

A hosted MCP server at mcp.honeycomb.io that exposes Honeycomb datasets, queries, traces and SLOs as tools, so an AI assistant can run the same high-cardinality investigations you would do in the query builder.

### Why is high cardinality the selling point?

Because most outages are specific — one customer, one build, one region — and pre-aggregated dashboards average that away. Honeycomb keeps raw dimensions queryable, and an agent that can enumerate columns will try breakdowns a human would not have thought to check.

### What key do I need?

A Honeycomb API key for the environment you want to query. Keys are scoped per environment, so an agent given a staging key simply cannot read production — which makes this a clean place to start conservatively.

### Does it work with OpenTelemetry data?

Yes. Honeycomb ingests OTLP, so if your services already emit OpenTelemetry traces the datasets are queryable through this server without any additional instrumentation work.

### Should I let an agent create triggers?

Read first. Alerting configuration is production configuration, and an agent that creates a noisy trigger costs your on-call rotation real sleep. Use it for investigation, and make alert changes a human decision.

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_Test this server across 40+ models on MCP Playground: https://mcpplaygroundonline.com/mcp-servers/honeycomb — free, no install._