---
title: "Rig MCP - Governed data access for Codex, Claude, Cursor, and AI Tools"
description: "Your AI tools are powerful; your data is walled off. Rig's MCP server gives Codex, Claude, Cursor, and any MCP tool governed access to your internal data."
canonical: "https://rig.so/uses/mcp"
format: markdown
---

# Your AI tools are powerful. Your data is locked behind walls they can't see

## Rig MCP gives Codex, Claude Code, Cursor, ChatGPT, and any AI tool governed access to your warehouse: schemas, metrics, joins, and live data through one protocol

## See Rig MCP in action

Watch an AI coding agent discover tables, resolve joins, and query a warehouse, all through Rig MCP.

For Data TeamsFor Business Teams

## One context layer, every AI tool

Any tool that supports MCP can discover your tables, understand your schema, and query your warehouse, without ever seeing raw credentials.

Claude Code

CLI agent for software engineering

Cursor

AI-native code editor

ChatGPT

Conversational AI assistant

Claude Cowork

Collaborative AI workspace

Any MCP client

Standard protocol, open ecosystem

[See how you can act on your data](https://rig.so/connect)

## How Rig MCP works

AI tool request

"Find tables related to subscription revenue and show me the join path to users"

search\_tables

get\_join\_path

→

Rig MCP server

Semantic search across 2,900+ tables

Resolve joins, lineage & sample values

RBAC permissions enforced per-query

Return only relevant context to the agent

→

Returned to agent

Schemas, column descriptions, join keys & sample data

Governed, read-only, auto-limited, and no raw warehouse credentials ever leave Rig

17

Rig MCP tools available

\<10ms

Sandbox SQL validation

-90%

Warehouse compute overhead

## Built for safe, governed access

### OAuth

Every user's data access is managed via OAuth. Set and audit permissions and logs per user and per team.

### Pre-computed context

Metadata, embeddings, join graphs, and sample values served from an in-process database, with no runtime LLM calls for search.

### Sandbox-first SQL

All agent queries validated in a sandbox. Execution auto-limits and respects permissions.

## Common questions

What is Rig MCP?

An MCP (Model Context Protocol) server that gives AI tools, like Codex, Claude Code, Cursor, ChatGPT, and Claude Cowork, governed access to your warehouse: schemas, metrics, joins, and live data through one protocol, without ever exposing raw database credentials.

Which AI tools can connect to Rig over MCP?

Any tool that supports the Model Context Protocol. Rig exposes 17 MCP tools for semantic table search, join and lineage resolution, and sandboxed querying, so the agent gets exactly the context it needs and nothing more.

How does Rig keep warehouse access safe?

Role-based access control is enforced on every query, all SQL is validated in a sandbox in under 10ms and auto-limited, access is managed via OAuth, and raw credentials never leave Rig. Every request is permissioned and logged for audit.

Does connecting via MCP add load to our warehouse?

No. Context such as metadata, embeddings, join graphs, and sample values is pre-computed and served from an in-process database, cutting warehouse compute overhead by around 90%, with no runtime LLM calls needed for search.

## Ready to give your AI tools real data access?

[Try Rig](https://app.rig.so/signup)

---

- [This page as HTML](https://rig.so/uses/mcp)
- [Site map for language models](https://rig.so/llms.txt)
- [API and agent documentation](https://rig.so/developers)