Agents & MCP
Giving AI agents and copilots governed numbers.
Agents & MCPGrounding a support copilot in certified customer health metrics
How a support copilot answers an account-health question from certified metrics, with sample schema, model and queries that separate ticket volume from open critical escalations.
Agents & MCPSelf-hosting regulated AI agents without leaking warehouse credentials
How a healthcare compliance team gave LLM agents access to clinical treatment analytics inside a private VPC without exposing database passwords.
Agents & MCPSlack bot weekly results: certified metrics for operations
How operations teams connect Slack bots to certified metrics using Model Context Protocol and query time zones in a thin semantic layer.
Agents & MCPGrounding copilots on governed metrics
Ground copilots on certified metrics so natural-language answers inherit governance instead of table dumps.
Agents & MCPAgent wrong numbers: five failure modes
A composite war story — five failure modes that show up when agents get put on metrics before the rails are ready, and how a governed path changes the ending.
Agents & MCPDesigning MCP tools agents cannot misuse
MCP makes it easy to expose too much. datahashi treats MCP tool design as safety engineering — small verbs, strict schemas, fail-closed validation.
Agents & MCPConnect Cursor to governed metrics via MCP
Connect Cursor to governed metrics over MCP — catalog discovery and typed queries for coding agents, without raw warehouse access.
Agents & MCPMCP for warehouse data without raw table access
How agents can query governed metrics through MCP without seeing raw warehouse tables or writing SQL.
Agents & MCPLimits, defaults, and agent-safe query shapes
Agents ask for everything by default. datahashi ships agent-safe limits so the first query an agent runs is already bounded, typed, and reviewable.
Agents & MCPWhy LLMs invent joins (and how to stop them)
Explain why models invent joins from schemas and how governed metrics remove join invention from the agent loop.
Agents & MCPWhat is a semantic layer (and why agents need one)
A semantic layer gives agents stable metric definitions, governed access, and one query shape so AI systems stop inventing their own numbers.
Agents & MCPMulti-tool MCP chaos: one revenue definition
A composite war story about conflicting revenue answers across MCP tools and how one certified metric restored trust.
Agents & MCPBuild an internal data agent on certified metrics
Build an internal data agent that only answers from certified metrics via MCP, with a clear eval for same-number trust.
Agents & MCP