io.github.DataAssistIO/Dataassist-IO
Query your org's data in natural language — read-only MCP access to SQL, NoSQL, files & warehouses.
Installation
Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).
claude mcp add --transport http dataassist-io 'https://app.dataassist.io/mcp'{
"mcpServers": {
"dataassist-io": {
"type": "http",
"url": "https://app.dataassist.io/mcp"
}
}
}Documentation
Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.
Sommaire
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.
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/mcpClaude 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.
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
- Create an account and your organization.
- Connect a data source — upload a CSV or connect a database/warehouse from the dashboard.
- Expose tables to your team and add curated metadata (optional but improves answer quality).
- Add the connector in your LLM client using the endpoint above and sign in.
- 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.
Questions fréquentes
Qu'est-ce que io.github.DataAssistIO/Dataassist-IO ?
Query your org's data in natural language — read-only MCP access to SQL, NoSQL, files & warehouses.
Comment installer io.github.DataAssistIO/Dataassist-IO ?
Il fonctionne comme serveur distant. Dans Claude Code : claude mcp add --transport http dataassist-io 'https://app.dataassist.io/mcp'. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.
Faut-il une clé API pour io.github.DataAssistIO/Dataassist-IO ?
Son entrée au registre n'indique aucune clé ni secret obligatoire. Certaines fonctions peuvent tout de même demander un compte auprès du service auquel il se connecte.
io.github.DataAssistIO/Dataassist-IO est-il open source ?
Son code est public sur GitHub, mais le dépôt ne déclare pas de licence standard.
Qui maintient io.github.DataAssistIO/Dataassist-IO ?
Il est publié par DataAssistIO. AI.tn le référence sans le maintenir ni le recommander.
Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.