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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

Query your org's data in natural language — read-only MCP access to SQL, NoSQL, files & warehouses.

README.md

DataAssist-IO MCP Server

Connect your databases, files, and warehouses to Claude, ChatGPT, and any MCP-compatible client — and let your team query them in plain language, safely and read-only.

![Website](https://dataassist.io) ![MCP Registry](https://registry.modelcontextprotocol.io) ![Endpoint](https://app.dataassist.io/mcp) ![ChatGPT App](https://chatgpt.com/apps/dataassist-io/asdk_app_6a26ec50353c8191b5774172b9a972cb)

DataAssist-IO is a hosted, multi-tenant Model Context Protocol server. Your organization signs up, connects its data sources, and your users query that data through natural language in their favorite LLM client. No SQL knowledge required for end users; no data copied or exposed beyond what you explicitly grant.

This is a remote MCP server — there is nothing to install or run yourself. You connect to it over an authenticated URL.

---

Connection

| | | |---|---| | Endpoint | https://app.dataassist.io/mcp | | Transport | Streamable HTTP | | Auth | OAuth 2.1 (Dynamic Client Registration) |

You'll need a DataAssist-IO account and at least one connected data source. Sign up at dataassist.io →

Connect from Claude

In Claude (Desktop or web), add a custom connector pointing at:

https://app.dataassist.io/mcp

Claude will walk you through the OAuth sign-in. After you authorize, your org's tables appear as queryable tools.

Connect from ChatGPT

DataAssist-IO is available as a published ChatGPT app — no manual setup required:

Open the DataAssist-IO app in ChatGPT →

Launch it, sign in when prompted, and start querying your data.

Connect from any MCP client

Point any client that supports the Streamable HTTP transport with OAuth at the endpoint above. The server implements OAuth discovery (/.well-known/oauth-protected-resource), so compliant clients negotiate authentication automatically.

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What you can do

Once connected, the assistant can use these read-only tools against the tables your admin has exposed to you:

| Tool | Purpose | |------|---------| | list_tables | Discover the tables available to you | | describe_table | Inspect a table's columns and types | | get_table_metadata | Read curated descriptions, tags, and per-column docs | | get_sample_data | Preview a handful of rows | | query_data | Run a read-only SQL SELECT (MySQL, Postgres, BigQuery, Redshift) | | query_collection | Run a read-only aggregation pipeline (MongoDB, AWS DocumentDB) |

Every tool is read-only by construction — queries are validated as SELECT-only and run against read-only database sessions. Nothing your assistant does can modify or delete your data.

Supported data sources

  • Files: CSV, Excel, SFTP-delivered CSV
  • Databases: MySQL, PostgreSQL, MongoDB, AWS DocumentDB
  • Warehouses: Google BigQuery, Amazon Redshift

File-based sources are imported and stored as Apache Iceberg tables on your behalf; live databases and warehouses are queried in place — your data is never copied.

Security & governance

  • Per-organization isolation — every query is scoped to your org; tenants never see each other's data.
  • OAuth-authenticated — no shared API keys; identity is established per user.
  • Team-level table grants — admins control exactly which tables each team can reach.
  • Full audit trail — every tool call is logged, with optional SOC2-grade request/response capture.
  • Read-only enforcement — validated SELECT-only access plus read-only DB sessions, defense in depth.

---

Getting started

  1. Create an account and your organization.
  2. Connect a data source — upload a CSV or connect a database/warehouse from the dashboard.
  3. Expose tables to your team and add curated metadata (optional but improves answer quality).
  4. Add the connector in your LLM client using the endpoint above and sign in.
  5. Ask questions about your data in plain language.

Links

  • 🌐 Website: <https://dataassist.io>
  • 🔌 MCP endpoint: https://app.dataassist.io/mcp
  • 📖 Model Context Protocol: <https://modelcontextprotocol.io>

About this repository

This repository is the public home for the DataAssist-IO MCP server's registry listing. DataAssist-IO is a hosted service — the server runs in DataAssist-IO's infrastructure, so there is no code to clone or deploy here. For product questions or support, visit dataassist.io.

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