DBChat - Talk to Your Database using AI

Transform your database into an intelligent conversational partner. Ask questions in plain English, get instant answers, and create beautiful visualizations - all through Claude Desktop or any other MCP Client.

🌟 What is DBChat?

DBChat is a bridge that connects any MCP client like Claude Desktop, Gemini-CLI, etc to your database, enabling natural language database interactions. Instead of writing SQL queries, simply ask the chatbot questions about your data and get instant, intelligent responses.

Before DBChat:

SELECT c.name, COUNT(o.id) as order_count, SUM(o.total) as revenue 
FROM customers c 
LEFT JOIN orders o ON c.id = o.customer_id 
WHERE o.created_at >= '2024-01-01' 
GROUP BY c.id, c.name 
ORDER BY revenue DESC 
LIMIT 10;

With DBChat:

"Show me our top 10 customers by revenue this year"

🎯 Why Use DBChat?

🗣️ Natural Language Database Queries

Ask questions in plain English: "How many customers signed up last month?"
Get conversational responses: The LLM explains the data and provides businessInsights
No SQL knowledge required: Perfect for business users and analysts

📊 Instant Data Visualizations

Automatic chart creation: Claude generates beautiful charts from your data
Multiple chart types: Line charts, bar charts, pie charts, scatter plots, and more
Interactive businessInsights: Drill down into your data with follow-up questions

🔍 Smart Data Exploration

Database discovery: "What tables do we have?" "Show me the customer table structure"
Relationship understanding: The AI model explains how your tables connect
Data quality businessInsights: Find duplicates, missing data, and anomalies

💼 Business Intelligence Made Easy

Executive dashboards: "Create a sales summary for our board meeting"
Trend analysis: "Show me user growth over the past 6 months"
Performance metrics: "Which products are underperforming?"

✨ Advanced Features

DBChat now includes powerful features for interactive demos, onboarding, collaborative analysis, and sophisticated business intelligence workflows.

🚀 MCP Prompts Support

Revolutionary structured workflow system for guided database analysis and business intelligence.

Professional Business Scenarios: Pre-built scenarios for Retail/E-commerce, Finance/Banking, and Logistics with realistic business contexts
Interactive Demo Templates: Complete 15-20 minute guided workflows with:
- Business narratives with protagonists and deadlines
- Step-by-step analytical progression
- Multiple choice decision points
- Expected outcomes and insights for each step
Three Sophisticated Prompt Types:
- mcp-demo - Complete interactive demo with business scenarios
- business-intelligence - Comprehensive BI analysis framework
- database-analysis - Enhanced database exploration workflow
MCP Protocol Integration: Full compliance with MCP prompts protocol including prompts/list and prompts/get handlers
How to start: Use any prompt-aware MCP client and select from available structured prompts for guided analysis

🎯 Interactive Multiple Choice Workflow System

Sophisticated workflow engine for structured data exploration and analysis.

Structured Progressions: Step-by-step workflows with contextual multiple choice options
Scenario-Specific Content: Tailored workflows for retail, finance, and logistics business domains
State Management: Tracks user choices and workflow progression throughout analysis sessions
New MCP Tools:
- start_workflow - Initiates interactive analysis workflows with business context
- workflow_choice - Processes user selections and advances workflow steps
MCP Resources: workflow://status resource shows active workflow status and progress
Integration Ready: Seamlessly works with demo data setup and insights collection systems

🛠️ Automatic Demo Data Setup

Intelligent database population system for demonstrations and onboarding.

Realistic Business Scenarios: Choose from Retail, Finance, or Logistics domains
Database-Agnostic: Works across all supported database types and configurations
Comprehensive Data Models:
- Retail: Customers, Products, Orders, Inventory with realistic relationships
- Finance: Accounts, Transactions, Customers, Loans with financial data patterns
- Logistics: Shipments, Routes, Warehouses, Deliveries with supply chain data
Instant Setup: 2-3 related tables per scenario with 10-15 representative rows each
Sample Analytics: Pre-built queries and analysis examples for each scenario
Cleanup Capabilities: Automatic reset and cleanup functionality for fresh demonstrations

🧠 Enhanced Insights Collection System

Professional business intelligence capture and reporting system.

Structured Insight Model: Comprehensive insights with categories, priorities, timestamps, and metadata
append_insight Tool: Advanced tool for capturing structured business findings with:
- Content validation and sanitization
- Automatic categorization with visual indicators
- Priority assignment (high/medium/low)
- Security audit logging
Professional Memo Generation:
- Comprehensive Memos: Executive summaries, categorized findings, priority insights, timeline analysis
- Quick Summaries: Fast consumption format for rapid business updates
- Multi-format Support: Both detailed and summary formats available
MCP Resources Integration:
- insights://memo - Professional business intelligence report
- insights://summary - Quick overview of collected insights
- Dynamic resource discovery as insights are captured
Persistent Storage: Auto-save to JSON with load/restore capabilities and export functionality
Real-time Statistics: Live tracking of insight counts, categories, and analytical progress

🗃️ Supported Databases

DBChat works with virtually any database (as long as it has a JDBC driver)

Popular Databases

MySQL / MariaDB - Web applications and e-commerce
Oracle - Enterprise applications
PostgreSQL - Advanced applications and analytics
SQL Server - Microsoft environments
H2 - Testing and development
SQLite - Local applications and prototypes
HSQLDB - Testing and development

NoSQL & Caching

Redis - In-memory data store
MongoDB - Document-oriented database
Cassandra - Wide-column store

Analytics & Cloud

Snowflake - Cloud data platform
Databricks - Cloud data platform
Amazon Redshift - AWS data warehouse
Google BigQuery - Google analytics
ClickHouse - Real-time analytics

Flat-file Based Data

CSV Files - Spreadsheet data and exports
Excel Files - Can be exported to CSV and queried

See INSTALL.md for the complete list and build options.

🚀 Quick Start

Step 1: Download DBChat

Download the latest release from GitHub Releases:

dbchat-4.0.0.jar - Basic version (PostgreSQL, SQLite, H2, HSQLDB, CSV) <-- Start here
dbchat-4.0.0.jar - Standard version (add MySQL, MariaDB, ClickHouse)
dbchat-4.0.0.jar - Enterprise version (add Oracle, SQL Server, DB2)
dbchat-4.0.0.jar - Cloud Analytics version (add Redshift, Snowflake, BigQuery)
dbchat-4.0.0.jar - All databases included (400MB+)

NOTE: Advanced users can also build a custom jar with only the drivers you need. See INSTALL.md for details.

IMPORTANT: Make sure that you are properly LICENSED to use any JDBC driver you install. The DBChat license does not cover any third party code or binaries.

Step 2: Install Claude Desktop (similar setup for any other MCP client)

Download Claude Desktop (free)
Sign in with your Claude account
Important: The Claude website does not support MCP. For MCP only with Anthropic models you need to use Claude Desktop.

Step 2 (alternate):

If you are not using Claude Desktop but want to use another MCP client like Cursor, Windsurf, VS Code, Continue, etc then please refer to the MCP Setup document for more details

Step 3: Set Up Your Database Connection

Create a configuration file dbchat.conf:

# Basic database connection
DB_URL=jdbc:mysql://localhost:3306/your_database
DB_USER=your_username
DB_PASSWORD=your_password
DB_DRIVER=com.mysql.cj.jdbc.Driver

# Optional: Enable web interface (not needed for Claude desktop)
HTTP_MODE=false
HTTP_PORT=8080

Examples for Common/Popular Databases:

MySQL:

DB_URL=jdbc:mysql://localhost:3306/your_database
DB_USER=your_username
DB_PASSWORD=your_password
DB_DRIVER=com.mysql.cj.jdbc.Driver

PostgreSQL:

DB_URL=jdbc:postgresql://localhost:5432/your_database
DB_USER=your_username
DB_PASSWORD=your_password
DB_DRIVER=org.postgresql.Driver

SQLite:

DB_URL=jdbc:sqlite:/path/to/your/database.db
DB_USER=
DB_PASSWORD=
DB_DRIVER=org.sqlite.JDBC

H2 database (in memory - no database setup required):

DB_URL=jdbc:h2:mem:testdb
DB_USER=sa
DB_PASSWORD=
DB_DRIVER=org.h2.Driver

Oracle:

DB_URL=jdbc:oracle:thin:@localhost:1521:xe
DB_USER=system
DB_PASSWORD=password
DB_DRIVER=oracle.jdbc.driver.OracleDriver

Redis:

DB_URL=jdbc:redis://localhost:6379
DB_USER=
DB_PASSWORD=your_redis_password

DBchat

Install / Use

README