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MCP Database Server: AI-Driven Insights & Automation - MCP Implementation

MCP Database Server: AI-Driven Insights & Automation

MCP Database Server seamlessly integrates any database with LLMs, empowering real-time AI-driven insights and automated workflows for smarter business decisions." )

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59% of users reported increased productivity after just one week

About MCP Database Server

What is MCP Database Server: AI-Driven Insights & Automation?

Imagine your database has a personal assistant who speaks fluent "human." MCP Database Server is that over-caffeinated barista of data operations—it takes your natural language requests and brews up precise database actions. Currently hooked up to MongoDB, it’s the Swiss Army knife of database interaction, with plans to expand its caffeine-fueled support to PostgreSQL, CockroachDB, Redis, and more.

How to use MCP Database Server: AI-Driven Insights & Automation?

Step 1: Summon the Server

Clone the repository like a wizard casting "git clone" (no broomsticks required). Install dependencies, and suddenly you’ve got a database whisperer running on your machine.

Step 2: Configure Your Magic

Edit config files like a mad scientist: point it to your MongoDB, tweak response styles, and decide whether it should auto-respond to existential questions like "Why is the sky blue?" (pro tip: disable that).

Step 3: Speak Human, Get Results

Ask questions like "Show me sales last month" or "Find users over 30." The server translates into database queries faster than you can say "ORM."

MCP Database Server Features

Key Features of MCP Database Server: AI-Driven Insights & Automation?

  • Language-to-SQL Translator: "Find all users who ordered pizza in 2023" becomes a perfectly formed query
  • Auto-Documentation: Generates API docs while you procrastinate
  • Future Database Flavors: Coming soon: PostgreSQL (the coffee of databases) and Redis (the espresso shot)
  • Security Shields: Because even AI needs a firewall (unlike your ex’s password habits)

Use Cases of MCP Database Server: AI-Driven Insights & Automation?

Data Analysts:

"Plot revenue trends" → automatic chart generation + SQL export

Developers:

"Create a user with email [email protected]" → instantly generates API endpoints and DB migrations

Interns:

MCP Database Server FAQ

FAQ from MCP Database Server: AI-Driven Insights & Automation?

Is this secure?

Absolutely! We don’t let your database credentials date each other. Encryption is mandatory, and there’s even a "no-silly-queries" mode to block requests like "DELETE FROM life."

Can I use it for MySQL?

Not yet, but we’re negotiating with MySQL reps over Zoom coffee breaks. Follow GitHub for updates.

Will it replace my DBA?

No. It’s more like a DBA’s intern that never sleeps. You still need someone to handle backups and rage at when the server crashes.

Content

MCP Database Server

A Model Context Protocol (MCP) server implementation that allows Large Language Models (LLMs) to interact with various databases through natural language. Currently supports MongoDB, with plans to support:

  • PostgreSQL
  • CockroachDB
  • Redis
  • And more...

Features

  • Database operations through natural language
  • Currently supports MongoDB with features:
    • List all collections
    • Query documents with filtering and projection
    • Insert documents
    • Delete documents
    • Aggregate pipeline operations
  • Future support for other databases:
    • PostgreSQL: SQL queries, table operations
    • CockroachDB: Distributed SQL operations
    • Redis: Key-value operations, caching

Prerequisites

  • Node.js v20.12.2 or higher
  • Database (currently MongoDB, other databases coming soon)
  • Claude Desktop Application

Installation

  1. Clone the repository:
git clone https://github.com/manpreet2000/mcp-database-server.git
cd mcp-database-server
  1. Install dependencies:
npm install
  1. Build the TypeScript code:
npm run build

Configuration

To get started, you need to configure your database connection in your Claude Desktop configuration file:

MacOS

~/Library/Application\ Support/Claude/claude_desktop_config.json

Windows

%APPDATA%/Claude/claude_desktop_config.json

Add the following configuration to your claude_desktop_config.json:

{
  "mcpServers": {
    "database": {
      "command": "/path/to/node",
      "args": ["/path/to/mcp-database/dist/index.js"],
      "env": {
        "MONGODB_URI": "your-mongodb-connection-string"
      }
    }
  }
}

Replace:

  • /path/to/node with your Node.js executable path or just use node
  • /path/to/mcp-database with the absolute path to this repository
  • your-mongodb-connection-string with your MongoDB connection URL

Usage Examples

MongoDB Examples

  1. List all collections in your database:
Can you show me all the collections in my database?
  1. Get specific records from a collection:
Give me 2 records from the chargers collection
  1. Query with filters:
Show me all documents in the users collection where status is active
  1. Insert a document:
Add a new user to the users collection with name John and email [[email protected]](/cdn-cgi/l/email-protection)
  1. Delete a document:
Remove the user with email [[email protected]](/cdn-cgi/l/email-protection) from the users collection
  1. Aggregate data:
Show me the total count of users by status in the users collection

Available Tools

1. getCollections

Lists all collections in the connected database.

2. getCollection

Retrieves documents from a collection with optional query parameters:

  • collectionName: Name of the collection
  • limit: Maximum number of documents to return (default: 10, max: 1000)
  • query: MongoDB query object
  • projection: Fields to include/exclude

3. insertOne

Inserts a single document into a collection:

  • collectionName: Name of the collection
  • document: Document object to insert

4. deleteOne

Deletes a single document from a collection:

  • collectionName: Name of the collection
  • query: Query to match the document to delete

5. aggregate

Executes an aggregation pipeline:

  • collectionName: Name of the collection
  • pipeline: Array of aggregation stages
  • options: Optional aggregation options

Future Database Support

PostgreSQL

  • SQL query execution
  • Table operations
  • Schema management
  • Transaction support

CockroachDB

  • Distributed SQL operations
  • Multi-region support
  • Transaction management
  • Schema operations

Redis

  • Key-value operations
  • Caching mechanisms
  • Pub/sub operations
  • Data structure operations

Security

  • Never commit your database connection strings to version control
  • Use environment variables for sensitive information
  • Follow database-specific security best practices

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

License

MIT License - See LICENSE for details

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