Think inside your AI world.
Honeycomb through Unl
Honeycomb shows the trace and the latency behind it. Whether that spike breaches the SLO you promised is your threshold - and 'it's slower' isn't the same as 'it's a regression'.
Honeycomb through Unl measures trace latency and SLO state against the regression threshold the backend engineer has ratified, so 'is this a real breach?' comes back verdict-shaped, naming the margin still open.
What Honeycomb holds
What Honeycomb through Unl queries directly:
- Queries run across traces, metrics and logs
- Trigger and SLO state
- BubbleUp analysis isolating what's different about the outlier
- Boards recording past investigations
What the naked read gives you
Honeycomb through its MCP server lets an agent run real queries across traces, metrics and logs, check the current state of any Trigger or SLO, and use BubbleUp to isolate what's actually different about an outlier. That's Honeycomb's own investigative tooling, not a paraphrase of it. What it doesn't do is decide whether the latency it surfaces breaches a promise anyone made - the SLO burn rate is a number, and how much burn is tolerable before someone gets paged is a line the team drew, not one Honeycomb draws for them. The trace is slower. Whether that's a regression is a separate call.
The frame judges the data it is given; it does not verify the source’s accuracy.
What changes when Honeycomb is read measured
The backend engineer ratified in Unl that a latency change only counts as an SLO breach when p95 crosses the agreed threshold for two consecutive query windows - because a single spiky minute was triggering tickets nobody needed to act on.
'Is this a real SLO breach?' returns, measured: yes - p95 has held above the threshold for two windows running. Honeycomb supplied the trace query and the SLO burn state; your ratified rule supplied the two-window rule that turns a spike into a breach.
And back again
The SLO verdict writes back into Unl - the query, the p95 reading, the two-window rule it was measured against, and whether it held. That record becomes the backend engineer's reference the next time a spike shows up on the same service, so the threshold either gets confirmed by a second real event or gets revisited before it pages anyone again.
The answer comes back measured against what you already decided, and why.
The lane is live and open to this tool today: one box, paste anything. If it speaks MCP, Unl can reach it. Readings arrive unprompted, the data beside the criterion; Unl is a courier, not a warehouse, and keeps only your keys and the frame.
Questions people ask
Can AI tell me if a latency spike breaches our SLO?
Not by itself. Honeycomb through Unl reads the trace query and the SLO burn state; whether that counts as a breach depends on the two-window rule you ratified in Unl. A single spiky minute and a held two-window trend return different verdicts.
How do I connect Honeycomb to Claude?
Honeycomb hosts its own MCP server, documented at docs.honeycomb.io/integrations/mcp, with OAuth or a management API key for authentication. Pair that connection with Unl, which holds the SLO threshold the query result gets weighed against.
Does Unl create Boards or change a Trigger?
No. Honeycomb through Unl runs queries and checks Trigger and SLO state - that's the whole exchange. Creating a Board or editing a Trigger's configuration isn't part of what gets sent back to Honeycomb.
What this is
Think inside your AI world — you stay in command
Save the thoughts, decisions and targets worth keeping, each with its reasoning, carried into every AI session the moment they matter. A new unit of exchange between you and your AI: the Settled Why with standing that travels. Unprompted.
Your whole AI world. What you decided at the epicentre. It plugs into Claude, Claude Code, ChatGPT and Cursor as an MCP connector — quick to connect, in a couple of steps.
MCP native·Human settled·Model agnostic·Your data
Measured Context
Connect Unl to bring the right information into the moment.
Your sources, read against the criteria you set.
The full product, open. Free at launch.