CData Python Server

A generic Model Context Protocol (MCP) Server for CData Python Connectors.

Quick Start (Experienced Users)

# Clone and setup
git clone https://github.com/CDataSoftware/cdata-mcp-python.git
cd cdata-mcp-python
uv venv && uv pip install "mcp[cli]"

# Install your connector (from the project directory!)
uv pip install ./your-cdata-connector.whl

# Verify installation
uv pip list | grep cdata

# Test connection
export CONNECTOR_MOD="cdata.{datasource}"
export CONNECTION_STRING="InitiateOAuth=GETANDREFRESH;"  # Or your auth method
uv run python -c "from utils.get_connection import get_connection; print('✅ Connected!' if get_connection() else '❌ Failed')"

# Configure Claude Desktop (add to claude_desktop_config.json)
# Then restart Claude completely

Purpose

We created this MCP Server to allow LLMs (like Claude) to query live data from any of over 250+ sources (listed below) supported by CData Python Connectors (free Community Licenses for personal use).

CData Python Connectors connect to SaaS apps, NoSQL stores, and APIs by exposing them as relational SQL models.

This server wraps those connectors and makes their data available through a simple MCP interface, so LLMs can retrieve live information by asking natural language questions — no SQL required.

Prerequisites

System Requirements

• Python: 3.12 or higher
• Operating System: Windows, macOS, or Linux
• Package Manager: uv (for Python dependency management)

Required Components

1. UV Package Manager

   Install with pip:

   pip install uv
   

2. CData Python Connector

   You'll need a CData Python Connector for your specific data source. The connector name format is cdata.{datasource} (e.g., cdata.salesforce, cdata.jira, cdata.mongodb).

   • Download: Visit https://www.cdata.com/python/download/
   • Select: Choose your specific data source from the dropdown
   • License: Free 30-day trial or Community License available
   • Note: Save the downloaded wheel (.whl) or tarball (.tar.gz) file location

3. Connection Configuration

   Prepare your connection string with authentication details for your data source. Each connector has different requirements.

   Common Connection String Examples

   • Salesforce:

     # Full OAuth with domain
     InitiateOAuth=GETANDREFRESH;LoginURL=domain.my.salesforce.com;
     
     # Simplified OAuth (often works without LoginURL)
     InitiateOAuth=GETANDREFRESH;
     
     # Username/Password
     [email protected];Password=yourpass;SecurityToken=token;LoginURL=domain.my.salesforce.com;
     

   • MongoDB:

     Server=localhost;Port=27017;Database=mydb;User=myuser;Password=mypass;
     

   • MySQL:

     Server=myserver.com;Port=3306;Database=mydb;UID=myuser;PWD=mypass;
     

   • REST API:

     Format=JSON;URI=https://api.example.com/data;AuthScheme=OAuth;
     

   Find your connector's specific requirements at: https://cdn.cdata.com/help/{datasource}/pg_connectionprops.htm

Setup Guide

Step 1: Clone the Repository

git clone https://github.com/CDataSoftware/cdata-mcp-python.git
cd cdata-mcp-python

Step 2: Set Up Python Environment

1. Create the virtual environment:

   uv venv
   

   Note: With uv, you typically don't need to manually activate the virtual environment. The uv pip and uv run commands automatically use the .venv in the current directory.

2. Install MCP dependencies:

   uv pip install "mcp[cli]"
   

3. Verify the virtual environment is being used:

   uv pip list  # Should show it's using .venv in the current directory
   

Step 3: Install Your CData Connector

Install the CData Python Connector you downloaded earlier:

Windows:

uv pip install "C:\path\to\cdata_{datasource}_connector-23.0.xxxx-cp312-cp312-win_amd64.whl"

macOS/Linux:

uv pip install /path/to/cdata-{datasource}-connector-23.0.xxxx-py3-none-any.whl

Example for Salesforce:

uv pip install ./cdata_salesforce_connector-23.0.8691-py3-none-any.whl

Important: Always run uv pip commands from the project directory to ensure packages are installed in the correct virtual environment. You can verify the installation with:

uv pip list | grep cdata

Step 4: Activate Your Connector License

Note: Some connectors may work without explicit license activation during initial testing. If you encounter license errors, follow the activation steps below.

Testing Your Setup

# test_connector.py
import os
os.environ['CONNECTOR_MOD'] = 'cdata.{datasource}'  # Replace with your connector
os.environ['CONNECTION_STRING'] = 'Your=Connection;String=Here;'

try:
    from utils.get_connection import get_connection
    conn = get_connection()
    cursor = conn.cursor()
    cursor.execute("SELECT * FROM sys_tables")
    tables = cursor.fetchall()
    print(f"Successfully connected! Found {len(tables)} tables.")
    for table in tables[:5]:  # Show first 5 tables
        print(f"  - {table[0]}")
    cursor.close()
    conn.close()
except Exception as e:
    print(f"Connection failed: {e}")

python test_connector.py

export CONNECTOR_MOD="cdata.{datasource}"  # Windows: set CONNECTOR_MOD=cdata.{datasource}
export CONNECTION_STRING="Your=Connection;String=Here;"  # Windows: set CONNECTION_STRING=...
uv run --active main.py

Starting server

Using the Server with Claude Desktop

Step 1: Configure Claude Desktop

Create or edit the Claude Desktop configuration file:

• Windows: %APPDATA%\Claude\claude_desktop_config.json
• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Linux: ~/.config/Claude/claude_desktop_config.json

Add your MCP server configuration:

{
    "mcpServers": {
        "salesforce_server": {
            "command": "uv",
            "args": [
                "--directory",
                "/absolute/path/to/cdata-mcp-python",
                "run",
                "--active",
                "main.py"
            ],
            "env": {
                "CONNECTOR_MOD": "cdata.salesforce",
                "CONNECTION_STRING": "InitiateOAuth=GETANDREFRESH;LoginURL=mycompany.my.salesforce.com;"
            }
        }
    }
}

Important Notes:

• Replace salesforce_server with a descriptive name for your data source
• Use the absolute path to your cloned repository directory
• Replace cdata.salesforce with your actual connector module name
• Use your actual connection string (keep it secure!)

Step 2: Restart Claude Desktop

1. Fully quit Claude Desktop (not just close the window):

   • Windows: Right-click system tray icon → Quit
   • macOS: Claude → Quit Claude (Cmd+Q)
   • Linux: Close and ensure process is terminated

2. Reopen Claude Desktop

3. Verify the server appears in the MCP servers list (look for the server icon)

Step 3: Test with Claude

Ask Claude questions about your data:

• "What tables are available in my Salesforce instance?"
• "Show me the first 5 records from the Account table"
• "What fields are in the Contact table?"

Usage Details

Once the MCP Server is configured, the AI client will be able to use the built-in tools to read, write, update, and delete the underlying data. In general, you do not need to call the tools explicitly. Simply ask the client to answer questions about the underlying data system. For example:

• "What is the correlation between my closed won opportunities and the account industry?"
• "How many open tickets do I have in the SUPPORT project?"
• "Can you tell me what calendar events I have today?"

The list of tools available and their descriptions follow:

Available Tools

The MCP server provides these tools to Claude for interacting with your data:

Troubleshooting

uv pip list | grep cdata
# ✅ Should show: cdata-{datasource}-connector

# ✅ Successful connection shows:
Successfully connected! Found X tables.
  - TableName1
  - TableName2
  ...

uv run --active main.py
# ✅ Should show: Starting server
# (Server will wait for connections - this is normal)

Getting Help

If you're still having issues:

1. Check connector documentation: https://cdn.cdata.com/help/{datasource}/
2. Join CData Community: https://community.cdata.com
3. Report MCP server issues: Create an issue in this repository
4. Contact CData support: For connector-specific problems

License

This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.

Supported Sources