semvec/pypi-packages huggingface dataset:
iflow-mcp_systems-mcp 0.1.0
Add your description here
Requires Python: >=3.13

# systems-mcp

[systems-mcp](https://github.com/lethain/systems-mcp) is an MCP server for interacting with
the [`lethain:systems`](https://github.com/lethain/systems/) library for systems modeling.

It provides two tools:

* `run_systems_model` runs the `systems` specification of a systems model.
    Takes two parameters, the specification and, optionally, the number of
    rounds to run the model (defaulting to 100).
* `load_systems_documentation` loads documentation and examples into the context window.
    This is useful for priming models to be more helpful at writing systems models.

It is intended for running locally in conjunction with Claude Desktop or a similar tool.

## Usage


Here's an example of using `systems-mcp` to run and render a model.

![Example of prompt for  using systems-mcp](docs/systems-mcp-prompt.png)

Here is the artifact generated from that prompt, including the output from
running the systems model.

![Example of artifact for using the output of systems-mcp](docs/systems-mcp-artifact.png)

Finally, here is an example of using the `load_systems_documentation` tool to prime
the context window and using it to help generate a systems specification.
This is loosely equivalent to including [`lethain:systems/README.md`](https://raw.githubusercontent.com/lethain/systems/refs/heads/master/README.md) in the context window,
but also includes a handful of additional examples
(see the included files in [./docs/](./docs/).

![Example prompt of loading documentation into context window](docs/sys-mcp-load-prompt.png)

Then you can render the model as before.

![Example prompt of rendering the generated model](docs/sys-mcp-load-artifact.png)

The most interesting piece here is that I've never personally used `systems` to model a social network,
but the LLM was able to do a remarkably decent job at generating a specification despite that.


## Installation

These instructions describe installation for [Claude Desktop](https://claude.ai/download) on OS X.
It should work similarly on other platforms.

1. Install [Claude Desktop](https://claude.ai/download).
2. Clone [systems-mcp](https://github.com/lethain/systems-mcp) into
    a convenient location, I'm assuming `/Users/will/systems-mcp`
3. Make sure you have `uv` installed, you can [follow these instructions](https://modelcontextprotocol.io/quickstart/server)
4. Go to Cladue Desktop, Setting, Developer, and have it create your MCP config file.
    Then you want to update your `claude_desktop_config.json`.
    (Note that you should replace `will` with your user, e.g. the output of `whoami`.

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

    Then add this section:

        {
          "mcpServers": {
            "systems": {
              "command": "uv",
              "args": [
                "--directory",
                "/Users/will/systems-mcp",
                "run",
                "main.py"
              ]
            }
          }
        }

5. Close Claude and reopen it.
6. It should work...
iflow-mcp_email-checker-mcp 0.1.0
Email validation MCP tool
Requires Python: >=3.10

# Email Checker MCP Server

For your cold outbound email, this tool will help you validate email addresses.

## Features

- Email address validation
- Simple JSON response format
- No API key required

## Prerequisites

- Python 3.x

## Installation

1. Clone the repository:
```bash
git clone https://github.com/ravinahp/email-checker-mcp.git
cd email-checker-mcp
```

2. Install dependencies using uv:
```bash
uv sync
```

Note: We use `uv` instead of pip since the project uses `pyproject.toml` for dependency management.

## Configure as MCP Server

To add this tool as an MCP server, you'll need to modify your Claude desktop configuration file.

The configuration file location depends on your operating system:

- MacOS: `~/Library/Application\ Support/Claude/claude_desktop_config.json`
- Windows: `%APPDATA%/Claude/claude_desktop_config.json`

Add the following configuration to your JSON file:

```json
{
    "email-checker-mcp": {
        "command": "uv",
        "args": [
            "--directory",
            "/Users/YOUR_USERNAME/Code/email-checker-mcp",
            "run",
            "email-checker-mcp"
        ]
    }
}
```

⚠️ IMPORTANT: 
1. Replace `YOUR_USERNAME` with your actual system username
2. Make sure the directory path matches your local installation

## Usage

The service provides a FastMCP tool for validating email addresses:

```python
@mcp.tool()
async def validate_email(email: str) -> bool:
    """Validate if an email address exists."""
```
## Example Use: 
Prompt: Does this email exist? 
<img width="769" alt="Screenshot 2025-01-08 at 10 14 43 AM" src="https://github.com/user-attachments/assets/1bee703b-3a8a-4ed0-ab0d-27b0dfdd06de" />



### Parameters:
- `email`: String containing the email address to validate

### Example Response:
```json
{
    "exist": true
}
```

## API Usage Limits

The service uses 2IP's Email API which provides:
- No API key required


## Error Handling

The service includes error handling for:
- Invalid email format
- API request failures
- Network timeouts
- Rate limiting
teachers-gitlab 0.4.0
CLI for mass actions on GitLab
Requires Python: >=3.8
Keywords: teaching, gitlab

# Teachers GitLab: perform operations over multiple GitLab projects

A Python utility to help you manage multiple repositories at once.

Our target users are teachers that need to manage separate repository for each
student and massively fork, clone or upload files in all projects at once.


## Installation in a nutshell

```shell
pip install teachers-gitlab
```

Note: we require at least `pip install pip==22.0`; details are in
our documentation at <https://teachers-gitlab.readthedocs.io/install.html>.


## First steps

Please, refer to our on-line documentation at
<https://teachers-gitlab.readthedocs.io/first-steps.html>.
Individual commands are described at
<https://teachers-gitlab.readthedocs.io/commands/>.


## Development

Please, look at <https://teachers-gitlab.readthedocs.io/development.html>.


## Contributing and getting help

Please, open an issue or start a discussion at our
GitHub repository <https://github.com/d-iii-s/teachers-gitlab>.
Matfyz members can create issues on
our GitLab as well <https://gitlab.mff.cuni.cz/teaching/utils/teachers-gitlab>.

We also welcome suggestions for new functions. Patches and merge requests
with new functions are welcomed even more :-).
reg-my-ip 0.0.1
A small package targeting to help on python project packaging process
Requires Python: >=3.11


# reg_my_ip

## Execution
Run through python interpreter:
```shell
python -m reg_my_ip -h
```

Run through python project script
```shell
reg-my-ip -h
```
## Development
The project requires `python` (3+ version) installed and `pip` ready for use on adding manage dependencies

#### Tools
|Name|Platform|Type|Description|
|---|---|---|---|
|install-dependencies.sh|shell|script| The scripts for installing depencies required|
|build.sh|shell|script| The scripts for build the package|
|build-and-deploy.sh|shell|script| The scripts for build and deploy the package|

* install-dependencies.sh
The script will install dependencies listed in `dev-requirements.txt` and `requirements.txt`. The first requirement file contains the dependencies for development like build and deploy tools. The second requirement file defined all required dependencies for the making the package works (**actual dependencies**).

## Useful Scripts
### Project Versioning
For version update in `pyproject.toml`.
This project use package [`xh-py-project-versioning`](https://github.com/xh-dev/xh-py-project-versioning) to manipulate the project version.

Simple usage includes:\
Base on current version, update the patch number with dev id
`python -m xh_py_project_versioning --patch` \
In case current version is `0.0.1`, the updated version will be `0.0.2-dev+000` 

To prompt the dev version to official version use command.
`python -m xh_py_project_versioning -r`.
Through the command, version `0.0.2-dev+000` will be prompt to `0.0.2` official versioning.

Base on current version, update the patch number directly
`python -m xh_py_project_versioning --patch -d` \
In case current version is `0.0.1`, the updated version will be `0.0.2` 

Base on current version, update the minor number directly
`python -m xh_py_project_versioning --minor -d` \
In case current version is `0.0.1`, the updated version will be `0.1.0` 

Base on current version, update the minor number directly
`python -m xh_py_project_versioning --minor -d` \
In case current version is `0.0.1`, the updated version will be `1.0.0`