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    Custom Mcp Database

    2 stars
    Python
    Updated Jul 14, 2025

    Table of Contents

    • 1. Installation
    • 2. Running the MCP Server
    • 3. Database Configuration
    • Adding a Database Connection
    • Removing a Database Connection
    • Getting Help
    • 4. Integration with Code Agents
    • Gemini
    • Claude Desktop
    • Tool Configuration for AI Agents
    • For Claude Code
    • For Gemini

    Table of Contents

    • 1. Installation
    • 2. Running the MCP Server
    • 3. Database Configuration
    • Adding a Database Connection
    • Removing a Database Connection
    • Getting Help
    • 4. Integration with Code Agents
    • Gemini
    • Claude Desktop
    • Tool Configuration for AI Agents
    • For Claude Code
    • For Gemini

    Documentation

    MCP Database Server

    This project provides a Middleware/Control Plane (MCP) server that allows code agents (like Gemini, Claude Desktop, and Claude Code) to securely execute queries against various databases (PostgreSQL, MySQL, MongoDB, Oracle) without directly exposing credentials. Database connection configurations are managed within an SQLite database (mcp_config.sqlite3).

    1. Installation

    To set up the project, follow these steps:

    1. Clone the repository (if you haven't already):

    bash
    git clone 
        cd custom-mcp-database

    2. Install dependencies:

    This project uses a venv (virtual environment) to manage dependencies. Run the following command to create the virtual environment and install the required Python packages:

    bash
    make install

    This will create a venv/ directory and install everything listed in requirements.txt.

    2. Running the MCP Server

    To start the MCP server, use the make run command:

    bash
    make run

    The server will start and listen for incoming requests from your code agents.

    3. Database Configuration

    Database connections are stored in mcp_config.sqlite3. You can manage these connections using the global mcp-db command (recommended) or the local main.py script.

    Adding a Database Connection

    Use the add-db command. The required parameters vary by database type.

    General Syntax (Global Command - Recommended):

    bash
    mcp-db add-db --alias  --type  [connection_parameters]

    Alternative (Local Command):

    bash
    python main.py add-db --alias  --type  [connection_parameters]

    Examples (Global Command):

    • PostgreSQL:
    bash
    mcp-db add-db --alias pg_dev --type postgres --host localhost --port 5432 --user myuser --password mypassword --dbname mydb
    • MySQL:
    bash
    mcp-db add-db --alias mysql_prod --type mysql --host 192.168.1.10 --port 3306 --user root --password secret --dbname production_db
    • Oracle:
    bash
    mcp-db add-db --alias oracle_test --type oracle --host oracle.example.com --port 1521 --user system --password oraclepass --dbname ORCLPDB1
    • MongoDB:
    bash
    mcp-db add-db --alias mongo_cluster --type mongo --uri "mongodb+srv://user:pass@cluster.mongodb.net/" --dbname myapp_db

    Removing a Database Connection

    Use the remove-db command with the alias of the connection you want to remove:

    Global Command:

    bash
    mcp-db remove-db --alias

    Local Command:

    bash
    python main.py remove-db --alias

    Example:

    bash
    mcp-db remove-db --alias pg_dev

    Getting Help

    For detailed help and examples:

    bash
    mcp-db --help
    mcp-db execute-query --help

    4. Integration with Code Agents

    Gemini

    Once the MCP server is running (make run), Gemini will automatically discover and make the following tools available for interacting with your configured databases:

    • list_aliases(): Lists all configured database aliases.
    • add_database(...): Adds a new database connection.
    • remove_database(...): Removes a database connection.
    • execute_query(database_alias, query, params, schema): Executes a query against a configured database.

    Gemini Usage Examples:

    • List aliases:
    code
    list_aliases()
    • Execute a SQL query (PostgreSQL/MySQL/Oracle):
    code
    execute_query(database_alias="pg_dev", query="SELECT * FROM users WHERE id = %s;", params={"id": 1})
    • Execute a MongoDB query:
    code
    execute_query(database_alias="mongo_cluster", query='''{"name": "John Doe"}''', params={"collection": "users"})

    Claude Desktop

    To integrate with Claude Desktop, you need to configure its claude_desktop_config.json file to point to your MCP server. Create or modify this file (usually located in your Claude Desktop configuration directory) with an entry similar to this:

    json
    {
      "mcpServers": {
        "Custom DB Server": {
          "command": "/your-path-to/custom-mcp-database/venv/bin/python",
          "args": [
            "/your-path-to/custom-mcp-database/main.py"
          ],
          "workingDirectory": "/your-path-to/custom-mcp-database"
        }
      }
    }

    Important: Replace /your-path-to/custom-mcp-database with the actual absolute path to your custom-mcp-database directory.

    After configuring, restart Claude Desktop. The MCP tools will then be available for use within Claude Desktop.

    Tool Configuration for AI Agents

    To enable AI agents like Claude Code and Gemini to automatically discover and utilize the MCP server's tools, you need to configure them to launch or connect to the MCP server. This typically involves providing the path to the main.py script and specifying the working directory.

    Here are examples of how you might configure your AI agent's mcpServers section:

    For Claude Code

    json
    {
      "mcpServers": {
        "Custom DB Server": {
          "command": "/your-path-to/custom-mcp-database/venv/bin/python",
          "args": [
            "/your-path-to/custom-mcp-database/main.py"
          ],
          "workingDirectory": "/your-path-to/custom-mcp-database"
        }
      }
    }

    For Gemini

    json
    {
      "mcpServers": {
        "Custom DB Server": {
          "command": "/your-path-to/custom-mcp-database/venv/bin/python",
          "args": [
            "/your-path-to/custom-mcp-database/main.py"
          ],
          "workingDirectory": "/your-path-to/custom-mcp-database"
        }
      }
    }

    Important: Replace /your-path-to/custom-mcp-database with the actual absolute path to your custom-mcp-database directory.

    Refer to your specific AI agent's official documentation for the most accurate and up-to-date instructions on configuring external MCP servers.

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