semvec/pypi-packages huggingface dataset:
rsamal-data-intelligence-mcp-server 0.0.5
MCP Server implementation for IBM Data Intelligence
Requires Python: >=3.11
Keywords: mcp, model-context-protocol, server, ai, fastmcp, watsonx-data-intelligence, ibm, watsonx, data-intelligence

# Data Intelligence MCP Server

The IBM Data Intelligence MCP Server provides a modular and scalable implementation of the Model Context Protocol (MCP), purpose-built to integrate with IBM Data Intelligence services. It enables secure and extensible interaction between MCP clients and IBM's data intelligence capabilities.

For the list of tools supported in this version and sample prompts, refer to [Tools](https://github.com/IBM/data-intelligence-mcp-server/blob/main/TOOLS.md).

Resources:
- [Integrating Claude with Watsonx Data Intelligence](https://community.ibm.com/community/user/blogs/ramakanta-samal/2025/10/01/integrating-claude-with-watsonx-data-intelligence) A step-by-step guide showing how Claude Desktop connects to the Data Intelligence MCP Server.
- [Watsonx Orchestrate + Data Intelligence](https://community.ibm.com/community/user/blogs/ramakanta-samal/2025/09/25/data) Demonstrates how Watsonx Orchestrate integrates with the MCP Server for automation.
---
## Quick Install

### Prerequisites
- Python 3.11 or higher
- Data Intelligence SaaS or CPD 5.2.1

### Installation

```bash
pip install ibm-watsonx-data-intelligence-mcp-server
```

Or with uv:

```bash
uvx ibm-watsonx-data-intelligence-mcp-server
```

## Documentation

For complete documentation, including:
- Detailed setup instructions
- Client configuration guides
- Server modes (HTTP, HTTPS, stdio)
- Environment configuration
- SSL/TLS setup
- Available tools and sample prompts

Please visit the [GitHub repository](https://github.com/IBM/data-intelligence-mcp-server).

## Basic Usage

### Run in stdio mode (recommended for local setup)
```bash
uvx ibm-watsonx-data-intelligence-mcp-server --transport stdio
```

### Run in HTTP mode
```bash
ibm-watsonx-data-intelligence-mcp-server --transport http --host 0.0.0.0 --port 3000
```

For more configuration options and detailed instructions, please refer to the [GitHub repository README](https://github.com/IBM/data-intelligence-mcp-server).
TPWUtils 0.2.0
A collection of Python 3 utilities for logging, threading, file monitoring, and geographic calculations
Requires Python: >=3.10
Keywords: logging, threading, inotify, great-circle, credentials, systemd

# This is a collection of my Python 3 utilities

- `Logger.py` set up a logger which supports console, rolling file, and/or SMTP logging methods
  - `addArgs(parser:argparse.ArgumentParser)` adds command line arguments for setting up logging
  - `mkLogger(args:argparse.ArgumentParser, fmt:str, name:str)` uses the args to setup the logger
    - *fmt* is the logging message format, by default "%(asctime)s %(threadName)s %(levelname)s: %(message)s"
    - *name* is the logger to setup

- `Thread.py` is a *threading.Thread* class which catches exceptions and sends them to a queue. Then the main thread can wait on the queue for a problem to arise in any of the threads.

- `INotify.py` is a thread which waits for modifications in a file system then forwards the modifications to a set of queues for other threads to process. It handles adding/removing of directories.

- `GreatCircle.py` calculates great circle distances on the earth in meters using Vincenty's method. Compared against Matlab's distance function, distance.sample.nc, it should give a maximum difference around 1e-7.

- `Credentials.py` loads credentials from YAML files with automatic prompting if the file doesn't exist
  - `getCredentials(fn:str)` returns a tuple of (username, password) from the specified YAML file

- `SingleInstance.py` ensures only one instance of a program runs at a time using Unix abstract sockets
  - Use as a context manager: `with SingleInstance(key) as single:`

- `loadAndExecuteSQL.py` loads and executes SQL commands from a file with optional table existence checking
  - `loadAndExecuteSQL(db, fn:str, tableName:str=None)` executes SQL from a file, skipping if table already exists

- `install.py` installs and manages systemd services and timers for both user and system contexts
  - `addArgs(parser:ArgumentParser)` adds command line arguments for service installation
  - `install(args:ArgumentParser)` installs services and timers
  - `uninstall(args:ArgumentParser)` removes services and timers

## License

This project is licensed under the GNU General Public License v3.0 - see the [LICENSE](LICENSE) file for details.