MCP Database Server

io.github.Souhar-dyaPublished by GitHub account Souhar-dyav1.3.1Updated Oct 24, 2026

MCP server for SQLite, PostgreSQL, and MySQL with natural language to SQL and direct SQL tooling.

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Overview

AI-generated overview

A local MCP server that exposes SQLite, PostgreSQL and MySQL databases to an assistant, turning natural-language questions into SQL and returning structured, in

What you can do
List tables and column counts in the connected database, and describe a table's schema in detail. Fetch sample rows from a table for a quick look at its contents. Submit a natural-language question and receive the generated SQL result as structured JSON. Check service health and status.
When to use it
Useful when you want an assistant to explore and query a relational database in plain language without writing SQL by hand, especially for read-only lookups, schema discovery and quick data samples.
Requirements
Runs as a local Docker container (or Python 3.11+ from source). Needs a reachable SQLite, PostgreSQL or MySQL database via DATABASE_URL, and MCP_API_KEY set to protect the database HTTP routes. Network access to the database host.
Before you install
DATABASE_URL contains real database credentials, so keep it out of Git, images and logs. MCP_API_KEY is a secret you generate and must protect. The README states only SELECT queries are allowed with validation and a 50-row limit, but the same README mentions CREATE, INSERT, UPDATE, DELETE and DROP being exercised in testing, so verify the read-only guarantee before pointing it at production data.

Installation

In SourceWeft

  1. Open MCP Database Server in the dashboard and add it to a workspace.
  2. 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

mcp-db-server

[License] [Python] [mcpindex verdict]

An MCP (Model Context Protocol) server that exposes relational databases (PostgreSQL/MySQL) to AI agents with natural language query support. Transform natural language questions into SQL queries and get structured results.

Features

  • Multi-Database Support: Works with PostgreSQL and MySQL
  • Natural Language to SQL: Convert plain English queries to SQL using HuggingFace transformers
  • RESTful API: Clean FastAPI-based endpoints for database operations
  • Safety First: Read-only operations with query validation and result limits
  • Docker Ready: Complete containerization with Docker Compose
  • Production Ready: Health checks, logging, and error handling
  • AI Agent Friendly: Designed specifically for AI agent integration

Version 1.4.0 Changes

  • Added mandatory X-API-Key authentication for all database HTTP endpoints; /health remains public for health checks.
  • Removed unrestricted credentialed CORS and made allowed origins explicitly configurable.
  • Changed the default HTTP bind address to 127.0.0.1.
  • Added table-name validation against existing database tables to block SQL injection through table routes.
  • Added PostgreSQL sslmode=require compatibility for asyncpg connections.
  • Updated Docker Compose, environment examples, and documentation for secure API-key configuration.
  • Published Docker images:
    • souhardyak/mcp-db-server:1.4.0
    • souhardyak/mcp-db-server:latest
  • Added GitHub Container Registry publishing for:
    • ghcr.io/souhar-dya/mcp-db-server:1.4.0
    • ghcr.io/souhar-dya/mcp-db-server:latest

API Endpoints

EndpointMethodDescription
/healthGETHealth check and service status
/mcp/list_tablesGETList all available tables with column counts
/mcp/describe/{table_name}GETGet detailed schema for a specific table
/mcp/queryPOSTExecute natural language queries
/mcp/tables/{table_name}/sampleGETGet sample data from a table

Quick Start

Option 1: Docker Compose (Recommended)

  1. Clone and start the services:

    bash
    git clone https://github.com/Souhar-dya/mcp-db-server.gitcd mcp-db-serverexport MCP_API_KEY="$(openssl rand -hex 32)"docker-compose up --build
  2. Test the endpoints:

    bash
    # Health checkcurl http://localhost:8000/health
    # List tables (requires the configured API key)curl -H "X-API-Key: $MCP_API_KEY" http://localhost:8000/mcp/list_tables
    # Describe a tablecurl -H "X-API-Key: $MCP_API_KEY" http://localhost:8000/mcp/describe/customers
    # Natural language querycurl -X POST "http://localhost:8000/mcp/query" \  -H "X-API-Key: $MCP_API_KEY" \  -H "Content-Type: application/json" \  -d '{"nl_query": "show top 5 customers by total orders"}'

Option 2: Local Development

  1. Prerequisites:

    • Python 3.11+
    • PostgreSQL or MySQL database
  2. Install dependencies:

    bash
    pip install -r requirements.txt
  3. Set environment variables:

    bash
    export DATABASE_URL="postgresql+asyncpg://user:password@localhost:5432/dbname"export MCP_API_KEY="$(openssl rand -hex 32)"# or for MySQL:# export DATABASE_URL="mysql+pymysql://user:password@localhost:3306/dbname"
  4. Run the server:

    bash
    python -m app.server

Sample Database

The project includes a sample database with realistic e-commerce data:

  • customers: Customer information (10 sample customers)
  • orders: Order records (17 sample orders)
  • order_items: Individual items within orders
  • order_summary: View combining order and customer data

Natural Language Query Examples

The server can understand various types of natural language queries:

bash
# Get all customerscurl -X POST "http://localhost:8000/mcp/query" \  -H "Content-Type: application/json" \  -d '{"nl_query": "show all customers"}'
# Count orders by statuscurl -X POST "http://localhost:8000/mcp/query" \  -H "Content-Type: application/json" \  -d '{"nl_query": "count orders by status"}'
# Top customers by order valuecurl -X POST "http://localhost:8000/mcp/query" \  -H "Content-Type: application/json" \  -d '{"nl_query": "top 5 customers by total order amount"}'
# Recent orderscurl -X POST "http://localhost:8000/mcp/query" \  -H "Content-Type: application/json" \  -d '{"nl_query": "show recent orders from last week"}'

Configuration

Environment Variables

VariableDescriptionDefault
DATABASE_URLFull database connection URLpostgresql+asyncpg://postgres:postgres@localhost:5432/postgres
DB_HOSTDatabase hostlocalhost
DB_PORTDatabase port5432
DB_USERDatabase usernamepostgres
DB_PASSWORDDatabase passwordpostgres
DB_NAMEDatabase namepostgres
HOSTServer host127.0.0.1
PORTServer port8000
MCP_API_KEYRequired API key for database HTTP routesNot set (API disabled)
CORS_ALLOW_ORIGINSComma-separated allowed browser originsEmpty (disabled)

Database Connection Examples

bash
# PostgreSQLDATABASE_URL=postgresql+asyncpg://user:pass@localhost:5432/mydb
# MySQLDATABASE_URL=mysql+pymysql://user:pass@localhost:3306/mydb
# PostgreSQL with SSLDATABASE_URL=postgresql+asyncpg://user:pass@localhost:5432/mydb?sslmode=require
### Database Connection Examples
```bash# PostgreSQL (local or cloud)DATABASE_URL=postgresql+asyncpg://user:password@host:5432/dbname
# MySQL (local or cloud)DATABASE_URL=mysql+aiomysql://user:password@host:3306/dbname
# PostgreSQL with SSL (cloud, e.g. Neon, Supabase, Aiven)DATABASE_URL=postgresql+asyncpg://user:password@host:5432/dbname?sslmode=require
# MySQL with SSL (cloud, e.g. Aiven, PlanetScale)DATABASE_URL=mysql+aiomysql://user:password@host:3306/dbname?ssl-mode=REQUIRED

Note:

  • For MySQL cloud providers, the ssl-mode parameter in the URL is ignored by the driver, but SSL is always enabled in the MCP server for cloud connections.
  • For PostgreSQL, use sslmode=require for cloud DBs. For MySQL, just use the standard URL; SSL is handled automatically.
  • If you see errors about ssl-mode or sslmode, check your URL and ensure you are using the correct driver prefix (mysql+aiomysql or postgresql+asyncpg).
Cloud Database Examples
bash
# Neon (PostgreSQL)DATABASE_URL=postgresql+asyncpg://username:[email protected]/dbname
# Aiven (MySQL)DATABASE_URL=mysql+aiomysql://avnadmin:[email protected]:11079/defaultdb?ssl-mode=REQUIRED
Docker Usage with Cloud DB
bash
docker run -d \  -p 8000:8000 \  -e DATABASE_URL="<your_cloud_database_url>" \  -e MCP_API_KEY="<your_random_api_key>" \  souhardyak/mcp-db-server:latest

GitHub Container Registry is also available:

bash
docker login ghcr.iodocker pull ghcr.io/souhar-dya/mcp-db-server:latestdocker run -d \  -p 8000:8000 \  -e DATABASE_URL="<your_database_url>" \  -e MCP_API_KEY="$MCP_API_KEY" \  ghcr.io/souhar-dya/mcp-db-server:latest

Images are published automatically when a v*.*.* tag is pushed. The workflow also creates the matching GitHub Release. To publish an existing tag such as v1.4.0, open the workflow's Run workflow action and enter 1.4.0. Set the GHCR package visibility to Public in the repository's Packages settings if unauthenticated pulls should be allowed.

Troubleshooting
  • If you get connect() got an unexpected keyword argument 'ssl-mode', ignore it: SSL is still enabled.
  • For network errors, check firewall and DB credentials.
  • For MySQL, always use mysql+aiomysql in the URL for async support.

### PostgreSQL SSL connection note
For PostgreSQL cloud providers, use an asyncpg URL and `sslmode=require`:
```bashDATABASE_URL=postgresql+asyncpg://user:password@host:5432/dbname?sslmode=require

The server normalizes sslmode=require to the ssl option expected by asyncpg. A temporary PostgreSQL verification was completed successfully against a compatible cloud database using CREATE, INSERT, SELECT, UPDATE, DELETE, and DROP; no test data was retained. Never commit or share a connection URL containing a real password.

API key authentication

MCP_API_KEY is a secret that you generate and provide to the server. It protects all database HTTP endpoints through the X-API-Key request header. The /health endpoint remains public for container health checks.

Generate a strong key on Linux or macOS:

bash
export MCP_API_KEY="$(openssl rand -hex 32)"

Generate one in Windows PowerShell:

powershell
$bytes = New-Object byte[] 32[Security.Cryptography.RandomNumberGenerator]::Create().GetBytes($bytes)$env:MCP_API_KEY = ([BitConverter]::ToString($bytes) -replace "-", "").ToLower()

Start the Docker image with the key:

bash
docker run -d \  -p 8000:8000 \  -e DATABASE_URL="<your_database_url>" \  -e MCP_API_KEY="$MCP_API_KEY" \  souhardyak/mcp-db-server:latest

Call a protected endpoint with the same key:

bash
curl -H "X-API-Key: $MCP_API_KEY" http://localhost:8000/mcp/list_tables

Keep the key in a password manager or deployment secret store. Do not commit it to Git, put it in a public image, or include it in logs.

Security Features

  • Mandatory HTTP Authentication: Database API routes require X-API-Key; /health remains public for health checks
  • Secure Network Default: HTTP mode binds to 127.0.0.1 unless explicitly configured otherwise
  • Restricted CORS: Cross-origin access is disabled unless origins are explicitly configured
  • Read-Only Operations: Only SELECT queries are allowed
  • Query Validation: Automatic detection and blocking of dangerous SQL operations
  • Result Limiting: Maximum 50 rows per query (configurable)
  • Input Sanitization: Protection against SQL injection
  • Safe Defaults: Secure configuration out of the box

Architecture

mcp-db-server/├── app/│   ├── __init__.py          # Package initialization│   ├── server.py            # FastAPI application and endpoints│   ├── db.py                # Database connection and operations│   └── nl_to_sql.py         # Natural language to SQL conversion├── .github/workflows/│   └── docker-publish.yml   # CI/CD pipeline├── docker-compose.yml       # Docker Compose configuration├── Dockerfile               # Container definition├── init_db.sql             # Sample database schema and data├── requirements.txt         # Python dependencies└── README.md               # This file

Model Context Protocol (MCP) Integration

This server is designed to work seamlessly with MCP-compatible AI agents:

  1. Standardized Endpoints: RESTful API following MCP conventions
  2. Structured Responses: JSON responses optimized for AI consumption
  3. Error Handling: Consistent error messages and status codes
  4. Documentation: OpenAPI/Swagger documentation available at /docs

Publish To VS Code MCP Store (Registry)

VS Code MCP gallery uses MCP Registry metadata. This repository now includes server.json for registry publication.

1) Build and publish Docker image

bash
docker build -t souhardyak/mcp-db-server:1.3.1 .docker push souhardyak/mcp-db-server:1.3.1

2) Validate server metadata

server.json is configured for an OCI package and stdio transport:

  • name: io.github.Souhar-dya/mcp-db-server
  • registryType: oci
  • identifier: docker.io/souhardyak/mcp-db-server:1.3.1

The Dockerfile includes registry ownership annotation:

  • io.modelcontextprotocol.server.name=io.github.Souhar-dya/mcp-db-server

3) Publish to MCP Registry

Install publisher and publish metadata:

bash
mcp-publisher login githubmcp-publisher publish

After publishing, users can discover/install it from MCP-compatible clients, including VS Code MCP experiences that read from the registry.

4) Local VS Code config example

json
{  "servers": {    "mcp-db-server": {      "type": "stdio",      "command": "docker",      "args": [        "run",        "--rm",        "-i",        "-e",        "DATABASE_URL=sqlite+aiosqlite:////data/default.db",        "souhardyak/mcp-db-server:1.3.1"      ]    }  }}

Docker Smoke Test

Use the dedicated Docker smoke test in tests/docker:

bash
python tests/docker/smoke_test.py

This verifies Docker daemon access, image build, container startup, and health status.

Deployment

Docker Hub

bash
# Pull the latest imagedocker pull souhardyak/mcp-db-server:latest
# Run with your databasedocker run -d \  -p 8000:8000 \  -e DATABASE_URL="your_database_url_here" \  souhardyak/mcp-db-server:latest

Kubernetes

yaml
apiVersion: apps/v1kind: Deploymentmetadata:  name: mcp-db-serverspec:  replicas: 3  selector:    matchLabels:      app: mcp-db-server  template:    metadata:      labels:        app: mcp-db-server    spec:      containers:        - name: mcp-db-server          image: souhardyak/mcp-db-server:latest          ports:            - containerPort: 8000          env:            - name: DATABASE_URL              valueFrom:                secretKeyRef:                  name: db-secret                  key: url---apiVersion: v1kind: Servicemetadata:  name: mcp-db-server-servicespec:  selector:    app: mcp-db-server  ports:    - port: 80      targetPort: 8000  type: LoadBalancer

Testing

Run Tests Locally

bash
# Start test databasedocker-compose up postgres -d
# Wait for database to be readysleep 10
# Run testspython -m pytest tests/ -v

Manual Testing

bash
# Test health endpointcurl http://localhost:8000/health
# Test table listingcurl http://localhost:8000/mcp/list_tables
# Test natural language querycurl -X POST "http://localhost:8000/mcp/query" \  -H "Content-Type: application/json" \  -d '{"nl_query": "show me all customers from California"}'

Contributing

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

📝 Changelog

v1.3.0 (2025-12-24) - Docker Path Fix

  • Fixed: Resolved import path issues in Docker container causing from db import DatabaseManager to fail
  • Fixed: Changed relative paths to absolute paths in Dockerfile and docker-compose.yml healthchecks
  • Improved: mcp_server.py now uses robust path resolution that works both locally and in Docker containers
  • Updated: Docker image rebuilt and pushed with all path fixes

v1.2.0 (2025-11-03) - MySQL Column Access Fix

  • Fixed: Resolved Could not locate column in row for column 'column_name' error with MySQL databases
  • Fixed: Changed describe_table method to use index-based row access for better SQLAlchemy compatibility
  • Improved: Enhanced cross-database compatibility for schema introspection
  • Resolved: GitHub Issue #1

v1.1.0 (2025-09-28) - Async Bug Fix

  • Fixed: Resolved str can't be used in 'await' expression error in MCP server
  • Improved: NLP query processing now works correctly with Claude Desktop integration
  • Enhanced: Added comprehensive test database setup scripts
  • Updated: Docker image rebuilt with bug fixes and updated dependencies

v1.0.0 (2025-09-25) - Initial Release

  • Initial: Full MCP Database Server implementation
  • Added: RESTful API with FastAPI
  • Added: Natural language to SQL conversion
  • Added: Docker containerization and deployment
  • Added: Multi-database support (PostgreSQL, MySQL, SQLite)

Acknowledgments

Support


⭐ If this project helped you, please consider giving it a star!

Source: README.md at commit 069028d

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v1.3.1LatestSep 16, 2026

Score

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