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Overview

CorralData MCP Server

The CorralData MCP Server is a Model Context Protocol (MCP) integration that lets AI assistants interact with the CorralData analytics platform. It provides 40 tools for exploring data, building dashboards, and managing analytics content — all through natural conversation.

What can it do?

Explore your data

  • Browse database schemas, tables, and columns

  • Discover foreign key relationships between tables

  • Search for tables by keyword

  • Execute read-only SQL queries against your data warehouse

Build dashboards

  • Create and update boards (dashboards)

  • Add and configure widgets (charts, tables, KPIs)

  • Set up board filters for interactive filtering

  • Bulk update widget layouts and properties

Manage datasets

  • List and inspect reusable dataset definitions

  • Create and update datasets with SQL queries

  • Validate widget queries before saving

Build Data Apps

  • Create custom HTML/JS widgets that run pre-registered SQL queries

  • Update a data app's content, queries, or sizing

  • Preview changes safely before persisting them

Work with connected services

  • List upstream services connected for a customer's data warehouse

  • Search and call tools exposed by connected third-party services

  • Write actions require explicit user confirmation before running

Configure AI behavior

  • List and read AskCorral's prompt templates

  • Set custom instructions that steer how AskCorral responds for a customer

  • List the customer accounts you have access to

How it works

The server runs as a stateless HTTP service exposing the MCP protocol. AI assistants like Claude and ChatGPT connect to the /mcp endpoint, discover available tools, and invoke them on behalf of the user.

Authentication is handled via OAuth 2.0 with Keycloak. Users authenticate once, and the server enforces role-based access — read-only tools are available to all authenticated users, while write operations require specific roles like board.edit or widget.edit.

Key features

  • Role-based access control — Write operations are restricted by role. Read operations are open to all authenticated users.

  • Token-efficient responses — Responses are designed for AI context windows with progressive disclosure (summaries for lists, details on demand).

  • SQL safety — Query execution is read-only with configurable row limits.

  • Schema discovery — AI assistants can explore your database schema to write accurate queries without prior knowledge of your data model.

Getting Started
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