
DBHub Analytics
io.github.amansingh63Published by GitHub account amansingh63v0.2.0Updated Oct 24, 2026
MCP server for Databricks, BigQuery, PostgreSQL, MySQL, SQL Server, SQLite, MariaDB
Overview
Lets an AI assistant run SQL and browse schemas across PostgreSQL, MySQL, MariaDB, SQL Server, SQLite, Databricks and BigQuery from one interface.
- What you can do
- DBHub Analytics is a local MCP server that connects MCP clients to one or more databases. Its main tools are execute_sql, which runs SQL with read-only enforcement and row limiting, and search_objects, which browses catalogs, schemas, tables, columns, indexes and routines. Reusable parameterized queries can be defined as custom tools in a dbhub.toml file, and multiple databases can be configured at once.
- When to use it
- Useful when an assistant should query or explore a database directly, for example asking questions of a Databricks or BigQuery warehouse in natural language, inspecting schemas, or running diagnostic queries against a read replica. It fits teams that want one server covering several database engines.
- Requirements
- Runs locally via npx (Node.js) or Docker. Needs connection details for each database: a DSN or the DB_HOST, DB_PORT, DB_NAME, DB_USER and DB_PASSWORD variables, plus DB_TYPE. Databricks and BigQuery need tokens or a service account key file; SSH tunneling needs SSH_HOST, SSH_PORT, SSH_USER and a key or password. Network access to the database is required.
Installation
In SourceWeft
- Open DBHub Analytics in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
DBHub Analytics
Universal Database MCP Server for Databricks, Google BigQuery, PostgreSQL, MySQL, SQL Server, SQLite, MariaDB
What is DBHub Analytics?
DBHub Analytics is an open-source MCP (Model Context Protocol) server that connects AI assistants like Claude Desktop, Claude Code, Cursor, VS Code Copilot, and other MCP-compatible clients to your databases. Query Databricks SQL warehouses, Google BigQuery datasets, PostgreSQL, MySQL, and more — all through a single unified interface.
Key Features
- Cloud Data Warehouses: Connect to Databricks SQL and Google BigQuery for analytics workloads
- Traditional Databases: Full support for PostgreSQL, MySQL, MariaDB, SQL Server, SQLite
- Multi-Database: Connect to multiple databases simultaneously with a single TOML config file
- Schema Explorer: Progressive disclosure — browse catalogs, datasets, schemas, tables, and columns
- Safety Guardrails: Read-only mode, row limits, and query timeouts to prevent runaway operations
- Secure Access: SSH tunneling, SSL/TLS encryption, and service account authentication
- Zero Config: Just provide a DSN — no drivers to install, no complex setup
Supported Databases
MCP Tools
Quick Start
NPM (recommended)
Databricks SQL
Google BigQuery
Docker
Demo Mode
Connect to Your AI Assistant
Claude Desktop / Claude Code
Add to your claude_desktop_config.json or .mcp.json:
GitHub Copilot (VS Code)
Add to your .vscode/mcp.json:
Cursor
Add to your Cursor MCP settings (~/.cursor/mcp.json):
Windsurf
Add to your Windsurf MCP config (~/.codeium/windsurf/mcp_config.json):
Multi-Database via TOML Config
For connecting to multiple databases, use a TOML config file with any of the above clients:
Configuration
DSN Connection Strings
Multi-Database Setup (TOML)
Connect to multiple databases simultaneously. Create a dbhub.toml file:
Then run:
See Multi-Database Configuration and Command-Line Options for complete documentation.
Use Cases
- Data Analysts: Ask Claude to query your Databricks or BigQuery data warehouse in natural language
- Backend Engineers: Explore database schemas, run diagnostic queries, and debug issues via AI
- DevOps/SRE: Connect to production read-replicas safely with read-only mode and row limits
- Data Scientists: Query multiple databases simultaneously — join insights across PostgreSQL and BigQuery
Development
Credits
Built on top of DBHub by Bytebase, an open-source database DevSecOps platform. Licensed under MIT.
Source: README.md at commit 3888599
Tools
0Version history
1- v0.2.0LatestSep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
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- Tools listed15 pts
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