MCP Database Server
Enables AI assistants to interact with PostgreSQL databases through query execution and schema inspection, supporting multiple schemas for customer data, document management, loan systems, and asset leasing.
README
MCP Database Server
A Model Context Protocol (MCP) server that provides PostgreSQL database access with query execution and schema inspection capabilities.
Overview
This MCP server enables AI assistants (like Claude) to interact with a PostgreSQL database containing data from multiple systems:
- cs (CustomerScoreView): Customer and credit assessment data
- dms (Data Management System): Document management data
- los (Loan Management System): Loan and payment data
- mls (Mahatheun Leasing System): Contract and asset leasing data
Features
- ✅ Query Execution: Execute SQL SELECT, INSERT, UPDATE, DELETE queries
- ✅ Schema Inspection: List schemas, tables, and column details
- ✅ Multi-Schema Support: Organize data by system (cs, dms, los, mls)
- ✅ Docker Setup: PostgreSQL in Docker with automatic initialization
- ✅ CSV Import: Sample data included and ready to import
Prerequisites
- Python 3.10 or higher
- Docker and Docker Compose
- pip (Python package installer)
Installation
-
Clone or navigate to the project directory:
cd c:\Users\chaya\project\mcp-database -
Install Python dependencies:
pip install -r requirements.txt -
Configure environment variables:
copy .env.example .envEdit
.envif you need to change database credentials (optional).
Setup
1. Start PostgreSQL Database
Start the PostgreSQL container with Docker Compose:
docker-compose up -d
Verify the database is running:
docker-compose ps
2. Verify Database Initialization
The database will automatically initialize with schemas and sample data. Check the schemas:
docker-compose exec postgres psql -U postgres -d mcp_database -c "\dn"
List tables in a schema:
docker-compose exec postgres psql -U postgres -d mcp_database -c "\dt cs.*"
3. (Optional) Import CSV Data
Sample CSV files are provided in raw_data/. To import them into the database:
docker-compose exec postgres bash -c "cd /raw_data && find . -name '*.csv' -type f"
Import a specific CSV file:
docker-compose exec postgres psql -U postgres -d mcp_database -c "\COPY cs.customers FROM '/raw_data/cs/customers.csv' WITH CSV HEADER;"
docker-compose exec postgres psql -U postgres -d mcp_database -c "\COPY dms.documents FROM '/raw_data/dms/documents.csv' WITH CSV HEADER;"
docker-compose exec postgres psql -U postgres -d mcp_database -c "\COPY los.loans FROM '/raw_data/los/loans.csv' WITH CSV HEADER;"
docker-compose exec postgres psql -U postgres -d mcp_database -c "\COPY mls.contracts FROM '/raw_data/mls/contracts.csv' WITH CSV HEADER;"
Running the MCP Server
Test Locally
Run the server directly to test:
python src/server.py
The server will start and listen for MCP messages via stdio.
Configure with Claude Desktop
To use this MCP server with Claude Desktop, add it to your Claude configuration file:
Windows: %APPDATA%\Claude\claude_desktop_config.json
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Add this configuration:
{
"mcpServers": {
"mcp-database": {
"command": "python",
"args": ["c:\\Users\\chaya\\project\\mcp-database\\src\\server.py"],
"env": {
"DB_HOST": "localhost",
"DB_PORT": "5432",
"DB_NAME": "mcp_database",
"DB_USER": "postgres",
"DB_PASSWORD": "postgres"
}
}
}
}
Restart Claude Desktop to load the server.
Available MCP Tools
1. list_schemas
Lists all available database schemas.
Example:
Can you list all database schemas?
2. list_tables
Lists all tables, optionally filtered by schema.
Parameters:
schema(optional): Schema name to filter (e.g., "cs", "dms", "los", "mls")
Example:
Show me all tables in the cs schema
3. describe_table
Get detailed column information for a specific table.
Parameters:
table_name(required): Name of the tableschema(optional): Schema name (default: "public")
Example:
Describe the structure of the customers table in the cs schema
4. execute_query
Execute a SQL query on the database.
Parameters:
query(required): SQL query stringparams(optional): Array of parameters for parameterized queries
Examples:
Query all customers with credit score above 700
SELECT * FROM cs.customers WHERE credit_score > 700
Get total loan amount by customer
SELECT customer_code, SUM(loan_amount) as total_loans
FROM los.loans
GROUP BY customer_code
Database Schema
cs (CustomerScoreView)
customers: Customer information and credit scorescredit_assessments: Credit assessment history
dms (Data Management System)
documents: Document metadata and storage infodocument_versions: Document version history
los (Loan Management System)
loans: Loan accounts and termspayments: Payment history
mls (Mahatheun Leasing System)
contracts: Lease contract informationassets: Asset details for leased itemslease_payments: Lease payment records
Project Structure
mcp-database/
├── src/
│ ├── server.py # Main MCP server
│ ├── database.py # Database connection manager
│ └── tools.py # MCP tool definitions
├── db/
│ └── init.sql # Database initialization script
├── raw_data/
│ ├── cs/ # CustomerScoreView CSV files
│ ├── dms/ # Data Management System CSV files
│ ├── los/ # Loan Management System CSV files
│ └── mls/ # Mahatheun Leasing System CSV files
├── docker-compose.yml # Docker configuration
├── requirements.txt # Python dependencies
├── pyproject.toml # Python project metadata
└── .env.example # Environment variable template
Troubleshooting
Docker container won't start
# Check logs
docker-compose logs postgres
# Restart container
docker-compose restart postgres
Connection refused error
- Ensure PostgreSQL is running:
docker-compose ps - Check port 5432 is not in use by another process
- Verify
.envfile has correct credentials
Import errors in Python
# Reinstall dependencies
pip install --upgrade -r requirements.txt
Development
To extend the server:
- Add new tools in
src/tools.py - Register handlers in
src/server.py - Update database schema in
db/init.sql - Add sample data in
raw_data/
License
This project is provided as-is for database integration purposes.
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