semvec/pypi-packages huggingface dataset:
universal-mcp-google-searchconsole 0.1.4
A Universal MCP Application: universal_mcp_google_searchconsole
License: MIT
Requires Python: >=3.11

# Google SearchConsole Universal MCP Server

This repository contains an implementation of an Google SearchConsole Universal MCP (Model Context Protocol) server. It provides a standardized interface for interacting with Google SearchConsole's SEO and backlink analysis tools through a unified API.

The server is built using the Universal MCP framework.

This implementation follows the MCP specification, ensuring compatibility with other MCP-compliant services and tools.

## Usage

You can start using Google SearchConsole directly from [agentr.dev](https://agentr.dev). Visit [agentr.dev/apps](https://agentr.dev/apps) and enable Google SearchConsole.

If you have not used universal mcp before follow the setup instructions at [agentr.dev/quickstart](https://agentr.dev/quickstart)

## Available Tools

The full list of available tools is at [./src/universal_mcp_google_searchconsole/README.md](./src/universal_mcp_google_searchconsole/README.md)

## Local Development

### 📋 Prerequisites

Ensure you have the following before you begin:

- **Python 3.11+** (recommended)
- **[uv](https://github.com/astral-sh/uv)** (install globally with `pip install uv`)

### 🛠️ Setup Instructions

Follow the steps below to set up your development environment:

1. **Sync Project Dependencies**

   ```bash
   uv sync
   ```

   This installs all dependencies from `pyproject.toml` into a local virtual environment (`.venv`).

2. **Activate the Virtual Environment**

   For Linux/macOS:

   ```bash
   source .venv/bin/activate
   ```

   For Windows (PowerShell):

   ```powershell
   .venv\Scripts\Activate
   ```

3. **Start the MCP Inspector**

   ```bash
   mcp dev src/universal_mcp_google_searchconsole/server.py
   ```

   This will start the MCP inspector. Make note of the address and port shown in the console output.

4. **Install the Application**
   ```bash
   mcp install src/universal_mcp_google_searchconsole/server.py
   ```

## 📁 Project Structure

```text
.
├── src/
│   └── universal_mcp_google_searchconsole/
│       ├── __init__.py       # Package initializer
│       ├── server.py            # Server entry point
│       ├── app.py            # Application tools
│       └── README.md         # List of application tools
├── tests/                    # Test suite
├── .env                      # Environment variables for local development
├── pyproject.toml            # Project configuration
└── README.md                 # This file
```

## 📄 License

This project is licensed under the [MIT License](LICENSE).

---

_Generated with **MCP CLI** — Happy coding! 🚀_
argparsenv 1.0.7
Extends python's argparser with environment variables
License: MIT
Requires Python: <4.0,>=3.11
Keywords: cli, environment, arguments

# argparsenv

This project extends python's argparse module to allow for environment variable overrides of command line arguments.

The rule for environment variable overrides is as follows:

1. If the argument is provided on the command line, the environment variable is ignored.
2. If the argument is not provided on the command line, the environment variable is used if it is set.
3. If the argument is not provided on the command line and the environment variable is not set, the default value is used.
4. If the argument is environment variable is set both on the command line and in the environment, the command line value is used.

## Installation

Stable release version:

```bash
pip install argparsenv
```

Latest development version:

```bash
pip install git+https://github.com/snaeil/argparsenv
```

## Usage

This module builds on top of python's standard library
[argparse](https://docs.python.org/3/library/argparse.html).

```python
import argparsenv

env_arg_parser = ArgumentParser()
env_arg_parser.add_argument(
    "--port",
    dest="port",
    env_var="MY_APP_DB_PORT",
    default="3306",
)
```

With this ArgumentParser instance, the port argument can be set in three ways:

1. On the command line:

```bash
python my_app.py --port 3307
```

2. As an environment variable (this can also be done by using a `.env` file):

```bash
export MY_APP_DB_PORT=3307
python my_app.py
```

3. Using the default value (here `3306`):

```bash
python my_app.py
```

## Contributing

Contributions are welcome!
For feature requests, bug reports or questions, please open an issue.
For code contributions, please open a pull request.

The development environment can be set up using `nix` and `devenv`:

1. Install nix package manager: `bash <(curl -L https://nixos.org/nix/install) --no-daemon`
2. Make sure, your `~/.config/nix/nix.conf` contains the following lines:
   ```nix
   experimental-features = nix-command flakes
   ```
3. Install [`devenv`](https://devenv.sh) by running:
   ```shell
   nix profile install --accept-flake-config 'nixpkgs#devenv'
   ```
4. Install [nix-direnv](https://github.com/nix-community/nix-direnv) by running:
   ```shell
   nix profile install 'nixpkgs#nix-direnv'
   ```
   Then add nix-direnv to `$HOME/.config/direnv/direnvrc`:
   ```bash
   source $HOME/.nix-profile/share/nix-direnv/direnvrc
   ```
5. Hook direnv into your shell by adding a line to your shell's configuration file (e.g. `~/.bashrc`),
   as described in the [direnv documentation](https://direnv.net/docs/hook.html):
6. You might have to open a new shell to make the changes take effect.
MPRAlib 0.6.5
Library to analyze count data of MPRA experiments.
License: MIT
Requires Python: >=3.8

# MPRAlib

![Tests](https://github.com/kircherlab/MPRAlib/actions/workflows/tests.yml/badge.svg?branch=master)
[![Coverage badge](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/kircherlab/MPRAlib/python-coverage-comment-action-data/endpoint.json)](https://htmlpreview.github.io/?https://github.com/kircherlab/MPRAlib/blob/python-coverage-comment-action-data/htmlcov/index.html)
[![PyPI version](https://badge.fury.io/py/MPRAlib.svg)](https://badge.fury.io/py/MPRAlib)
[![Bioconda Version](https://img.shields.io/conda/vn/bioconda/mpralib?label=bioconda)](https://bioconda.github.io/recipes/mpralib/README.html)

MPRAlib is a Python library and CLI for processing MPRA (Massively Parallel Reporter Assay) data.

## Installation

### PyPI

```bash
pip install MPRAlib
```

### Conda

```bash
conda install -c bioconda mpralib
```

## Usage

### Command Line Interface

Use the `mpralib` command to access various functionalities.

#### Validate a file

MPRAlib provides a CLI tool for validating MPRA data files against supported schemas.

```bash
mpralib validate-file <schema> --input <input_file>
```

- `<schema>`: One of `reporter-sequence-design`, `reporter-barcode-to-element-mapping`, `reporter-experiment-barcode`, `reporter-experiment`, `reporter-element`, `reporter-variant`, `reporter-genomic-element`, `reporter-genomic-variant`
- `<input_file>`: Path to your data file (e.g., `.tsv.gz`, `.bed.gz`)

**Example:**

```bash
mpralib validate-file reporter-sequence-design --input data/reporter_sequence_design.example.tsv.gz
```

### Python API

In general MPRAlib is ment to be used as a library. Please have a look at our notebook [mpralib.ipynb](https://github.com/kircherlab/MPRAlib/blob/master/examples/mpralib.ipynb) for a more detailed example.

## License

MIT License

## Links

- [Documentation](https://github.com/mschubach/MPRAlib)
- [Issues](https://github.com/mschubach/MPRAlib/issues)
nonebot-plugin-zssm 0.3.7
这是什么？问一下！用 ai 来解释群友发送的「未知」内容
License: MIT
Requires Python: >=3.12

<div align="center">
  <a href="https://v2.nonebot.dev/store"><img src="https://github.com/A-kirami/nonebot-plugin-template/blob/resources/nbp_logo.png" width="180" height="180" alt="NoneBotPluginLogo"></a>
  <br>
  <p><img src="https://github.com/A-kirami/nonebot-plugin-template/blob/resources/NoneBotPlugin.svg" width="240" alt="NoneBotPluginText"></p>
</div>

<div align="center">

# nonebot-plugin-zssm

_✨ 这是什么？问一下！ ✨_


<a href="./LICENSE">
    <img src="https://img.shields.io/github/license/owner/nonebot-plugin-zssm.svg" alt="license">
</a>
<a href="https://pypi.python.org/pypi/nonebot-plugin-zssm">
    <img src="https://img.shields.io/pypi/v/nonebot-plugin-zssm.svg" alt="pypi">
</a>
<img src="https://img.shields.io/badge/python-3.12+-blue.svg" alt="python">

</div>

## 📖 介绍

这是一个 nonebot2 的 ai 解释插件，对着你想要了解的东西，回复「zssm」吧！

## 💿 安装

<details open>
<summary>使用 nb-cli 安装</summary>
在 nonebot2 项目的根目录下打开命令行, 输入以下指令即可安装

    nb plugin install nonebot-plugin-zssm

</details>

<details>
<summary>使用包管理器安装</summary>
在 nonebot2 项目的插件目录下, 打开命令行, 根据你使用的包管理器, 输入相应的安装命令

<details>
<summary>pip</summary>

    pip install nonebot-plugin-zssm
</details>
<details>
<summary>pdm</summary>

    pdm add nonebot-plugin-zssm
</details>
<details>
<summary>poetry</summary>

    poetry add nonebot-plugin-zssm
</details>
<details>
<summary>conda</summary>

    conda install nonebot-plugin-zssm
</details>

打开 nonebot2 项目根目录下的 `pyproject.toml` 文件, 在 `[tool.nonebot]` 部分追加写入

    plugins = ["nonebot_plugin_zssm"]

</details>

## ⚙️ 配置

在 nonebot2 项目的`.env`文件中添加下表中的必填配置

| 配置项 | 必填 | 默认值 | 说明 |
|:-----:|:----:|:----:|:----:|
| zssm_ai_text_endpoint | 否 | https://api.deepseek.com/v1 | 解释使用的 ai 端点 |
| zssm_ai_text_token | 是 | 无 | 解释使用的 api-key |
| zssm_ai_text_model | 否 | deepseek-reasoner | 解释使用的模型 |
| zssm_ai_vl_endpoint | 否 | https://api.siliconflow.cn/v1 | 识图使用的 ai 端点 |
| zssm_ai_vl_token | 是 | 无 | 解释使用的 api-key |
| zssm_ai_vl_model | 否 | Qwen/Qwen2.5-VL-72B-Instruct | 解释使用的模型 |
| zssm_ai_check_endpoint | 否 | https://api.deepseek.com/v1 | 审查使用的 ai 端点 |
| zssm_ai_check_token | 否 | 无 | 审查使用的 api-key，不填则不进行审查 |
| zssm_ai_check_model | 否 | deepseek-v3 | 审查使用的模型 |
| zssm_browser_proxy | 否 | 无 | 浏览器代理 |
| zssm_install_browser | 否 | True | 启动时安装浏览器 |
| zssm_pdf_max_size | 否 | 10 | 最大pdf大小 |
| zssm_pdf_max_chars | 否 | 300000 | 最大字符数 |
| zssm_pdf_max_pages | 否 | 50 | 最大页数 |

## 🎉 使用
### 指令表
| 指令 | 权限 | 需要@ | 范围 | 说明 |
|:-----:|:----:|:----:|:----:|:----:|
| zssm | 无 | 否 | 回复 | 对着需要解释的东西回复一下 |

### 效果图

![05f21be5fdf0221fe8f13e64342ed622](https://github.com/user-attachments/assets/68e806b6-895e-41dd-a08e-303b1a2abcb3)

![8ef4fdfcf05161dcaf77a27cab1670b5](https://github.com/user-attachments/assets/496b26e3-3f93-4db1-8687-88a0637122ff)