semvec/pypi-packages huggingface dataset:
mediawiki-mcp-server 0.0.1
A MCP server for MediaWiki
Requires Python: >=3.13

# MediaWiki MCP Server 🚀

A MCP server that provides seamless interaction with Wikipedia's API. This tool allows you to search and retrieve Wikipedia content with LLMs 🤖!

https://github.com/user-attachments/assets/b5d9c5f3-a60e-48ea-8b4b-f1a7524d4fbb

## Features ✨

- 🔍 Search wiki pages with customizable wiki site. e.g. wikipedia.org, fandom.com, wiki.gg and more!
- 📖 Retrieve detailed page content

## Usage 💻

1. Ensure that uv is installed on your device.
2. Clone this repo and execute:

```bash
uv sync
```

3. Configure in your client:

Command:

```bash
uv
```

Args:

The server defaults to using <https://en.wikipedia.org/>. Also, you can make the server search other wiki sites!

To see if a wiki site works with this server, check if it uses MediaWiki software (usually shown by an icon at the bottom of the site).

To check further and find the endpoint (usually the website's domain, like <https://mediawiki.org/>), check by going to base-url/rest.php/v1/page in a browser (like <https://noita.wiki.gg/rest.php/v1/page>) and see if the output looks right. If not, add '/w' to the base URL and try again.

![](/imgs/PixPin_2025-04-04_19-41-55.png)

Then, set this endpoint as --base-url.

```bash
run
--directory
path/to/project/src/mediawiki_mcp_server
mediawiki-mcp-server
--base-url
https://example.com/
```

Envs:

```bash
HTTP_PROXY=http://host:port
```

## Supported Tools 🛠

### Search

```python
async def search(query: str, limit: int = 5)
```

- `query`: Search term (preferably short and focused)
- `limit`: Maximum number of results to return (default: 5)

### Get Page

```python
async def get_page(title: str)
```

- `title`: The exact title of the Wikipedia page to retrieve

## Development 👨‍💻

```bash
npx @modelcontextprotocol/inspector uv run mediawiki-mcp-server
```

Here's some document that might help:

- <https://www.mediawiki.org/api/rest_v1/>

## Contributing 🤝

This server is under development. Contributions are welcome! Feel free to submit issues and pull requests.
lbfgs-lab 0.0.3
L-BFGS variants for academic research
Requires Python: >=3.8

# lbfgs_lab

## Set Up

```bash
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt 
```

https://pypi.org/project/lbfgs_lab/

https://packaging.python.org/en/latest/tutorials/packaging-projects/

## Documentation

https://docs.readthedocs.com/platform/stable/tutorial/

## References

This project is partially inspired by the following L-BFGS-related repositories.
Thanks to the developers of these projects.

* [DirL-BFGS](https://github.com/ashkansl/DirL-BFGS): Direct L-BFGS method using a low-rank plus diagonal inverse Hessian approximation.
* [LBFGSpp](https://github.com/yixuan/LBFGSpp): Header-only C++ library for L-BFGS and L-BFGS-B algorithms.
* [liblbfgs](https://github.com/chokkan/liblbfgs): C library implementing the L-BFGS optimization method.
* [mL-BFGS](https://github.com/yuehniu/mL-BFGS?tab=readme-ov-file): Momentum-based L-BFGS for distributed large-scale neural network training.
* [paper-regularized-qn-benchmark](https://github.com/dmsteck/paper-regularized-qn-benchmark): Regularized L-BFGS approach for large-scale nonconvex minimization.
* [py-owlqn](https://github.com/samson-wang/py-owlqn.git): Python implementation of the OWL-QN optimization algorithm with a logistic regression example.
* [pylbfgs-dedupeio](https://github.com/dedupeio/pylbfgs): Python/Cython wrapper for the liblbfgs library.
* [pylbfgs-larsmans](https://github.com/larsmans/pylbfgs): Alternative Python/Cython wrapper for the liblbfgs library.
* [python_lbfgsb](https://github.com/avieira/python_lbfgsb): Pure Python implementation of L-BFGS-B, though using a deprecated scipy module.

## License

This project is licensed under the MIT License. (`liblbfgs` is under the MIT License as well).

See the [LICENSE](LICENSE) file for details.