Honeycomb MCP for AI agents

Runs at once (reads)

Looks things up in Honeycomb MCP without asking first. 23 actions.

• Canvas agent poll responsePoll for the result of a previously-issued canvas_agent_invoke call. Pass the investigation_id and session_id returned from canvas_agent_invoke. Each call waits up to wait_seconds (default 30, max 50)
• Find columnsSearch for columns and calculated fields by intent across one or all datasets in an environment. When to use: - "What column has the error rate?" / "Find columns related to duration or latency" — inte
• Find queriesSearch query history and saved queries by intent; returns matching queries with their run PKs. When to use: - "Has anyone queried the error rate for checkout?" — check existing work before composing a
• Get aiconversationFetch the full event timeline for a single AI conversation, identified by its OpenTelemetry gen_ai.conversation.id attribute value. Prefer this over ad-hoc run_query filtered by conversation ID — it r
• Get datasetGet dataset metadata and its full column schema (columns + calculated fields), sorted by most recent write activity. When to use: - "What columns does the api-service dataset have?" — retrieve the sch
• Get dataset columnsGet the full column schema for one dataset, with optional sample values for specific columns. When to use: - Validating column names before composing a run_query (check the column exists and note its
• Get environmentGet details for a specific environment, including its dataset list sorted by most recent activity. When to use: - After get_workspace_context returns environment slugs, drill into one to see which dat
• Get query resultsRetrieve results and metadata from an existing query execution. Accepts a Honeycomb URL, a run_pk, or a query_id (returns most recent run). Provide exactly one of these three inputs. When to use: - Af
• Get signalsReturns Anomaly Signals for the current team. An Anomaly Signal tracks a service in a dataset and detects when its behavior deviates from its historical baseline. Use this tool to investigate a specif
• Get span detailsSummarize attributes and their common values observed on spans with a specific name. USE THIS AFTER list_spans (or whenever you already know a span_name) and BEFORE run_query. It tells you which attri
• Get traceRetrieve all spans for a specific trace ID and render them as a waterfall. When to use: - User pastes a trace ID from logs, a Slack alert, or the Honeycomb UI — fetch it here. - Drilling into a specif
• Get triggersList triggers (alert rules) for the team, or fetch full configuration for a single trigger. When to use: - "What alerts are firing?" / "What triggers do we have?" — list mode (no trigger_id). - "Show