Honeydew semantic layer provides a governed, business-friendly data model that unifies metrics, dimensions, and relationships across sources
Honeydew semantic layer provides a governed, business-friendly data model that unifies metrics, dimensions, and relationships across sources, enabling consistent
Skills and tools powered by the Honeydew MCP that help coding agents build semantic models and analyze data through natural conversation.
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Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.
| Tool | What it does |
|---|---|
| model-exploration | Explore the semantic model — list entities, search fields, inspect relationships, and discover warehouse tables |
| workspace-branch | Manage workspaces and branches — set session context, create/delete branches, review branch history, and open pull requests |
| entity-creation | Create entities — the foundational business concepts built from data warehouse tables |
| relation-creation | Define relationships between entities with join types, cardinality, and complex join conditions |
| attribute-creation | Create calculated attributes (dimensions) — per-row virtual columns defined with SQL expressions |
| metric-creation | Create metrics (KPIs) — reusable aggregations like totals, averages, ratios, and growth rates |
| context-item-creation | Create context items — instructions, skills, knowledge pointers, and memory events that give the AI analyst persistent knowledge about your organization |
| domain-creation | Create domains — curated subsets of the semantic model exposed to specific teams or use cases |
| validation | Mandatory post-creation validation — type-specific sanity checks, cross-validation, and error handling |
| query | Query data using structured YAML perspectives, natural language questions, or multi-step deep analysis |
| query-debugging | Review and inspect past query executions — what ran, from which client (BI tools, SQL interface, MCP, deep analysis), the semantic YAML and compiled SQL behind a run, and debugging failures |
| filtering | Advanced filtering syntax — comparisons, string matching, date handling, nulls, and full-text search |
Give your coding agent the full DevTools toolbox: traces, network, console, heap snapshots and Lighthouse.
Workers, KV, R2 and D1 by conversation — Cloudflare's official remote servers for building and observability.
Dashboards, Prometheus and Loki queries, incidents and alerts — observability by conversation.
Errors with full context — stack traces, issue triage and AI-powered root-cause analysis from Sentry's server.
Connect Flutter applications with AI coding assistants via the Model Context Protocol.
Enables natural language interaction with Splunk Enterprise and Cloud for searching data and managing resources.