semvec/pypi-packages huggingface dataset:
universal-mcp-asana 0.1.1
A Universal MCP Application: universal_mcp_asana
License: MIT
Requires Python: >=3.11

# Asana Universal MCP Server

This repository contains an implementation of an Asana Universal MCP (Model Context Protocol) server. It provides a standardized interface for interacting with Asana'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 Asana directly from [agentr.dev](https://agentr.dev). Visit [agentr.dev/apps](https://agentr.dev/apps) and enable Asana.

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_asana/README.md](./src/universal_mcp_asana/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_asana/mcp.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_asana/mcp.py
   ```

## 📁 Project Structure

```text
.
├── src/
│   └── universal_mcp_asana/
│       ├── __init__.py       # Package initializer
│       ├── mcp.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! 🚀_
universal-mcp-sentry 0.1.1
A Universal MCP Application: universal_mcp_sentry
License: MIT
Requires Python: >=3.11

# Sentry Universal MCP Server

This repository contains an implementation of an Sentry Universal MCP (Model Context Protocol) server. It provides a standardized interface for interacting with Sentry'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 Sentry directly from [agentr.dev](https://agentr.dev). Visit [agentr.dev/apps](https://agentr.dev/apps) and enable Sentry.

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_sentry/README.md](./src/universal_mcp_sentry/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_sentry/mcp.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_sentry/mcp.py
   ```

## 📁 Project Structure

```text
.
├── src/
│   └── universal_mcp_sentry/
│       ├── __init__.py       # Package initializer
│       ├── mcp.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! 🚀_
universal-mcp-calendly 0.1.1
A Universal MCP Application: universal_mcp_calendly
License: MIT
Requires Python: >=3.11

# Calendly Universal MCP Server

This repository contains an implementation of an Calendly Universal MCP (Model Context Protocol) server. It provides a standardized interface for interacting with Calendly'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 Calendly directly from [agentr.dev](https://agentr.dev). Visit [agentr.dev/apps](https://agentr.dev/apps) and enable Calendly.

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_calendly/README.md](./src/universal_mcp_calendly/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_calendly/mcp.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_calendly/mcp.py
   ```

## 📁 Project Structure

```text
.
├── src/
│   └── universal_mcp_calendly/
│       ├── __init__.py       # Package initializer
│       ├── mcp.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! 🚀_
universal-mcp-posthog 0.1.1
A Universal MCP Application: universal_mcp_posthog
License: MIT
Requires Python: >=3.11

# Posthog Universal MCP Server

This repository contains an implementation of an Posthog Universal MCP (Model Context Protocol) server. It provides a standardized interface for interacting with Posthog'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 Posthog directly from [agentr.dev](https://agentr.dev). Visit [agentr.dev/apps](https://agentr.dev/apps) and enable Posthog.

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_posthog/README.md](./src/universal_mcp_posthog/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_posthog/mcp.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_posthog/mcp.py
   ```

## 📁 Project Structure

```text
.
├── src/
│   └── universal_mcp_posthog/
│       ├── __init__.py       # Package initializer
│       ├── mcp.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! 🚀_
universal-mcp-slack 0.1.1
A Universal MCP Application: universal_mcp_slack
License: MIT
Requires Python: >=3.11

# Slack Universal MCP Server

This repository contains an implementation of an Slack Universal MCP (Model Context Protocol) server. It provides a standardized interface for interacting with Slack'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 Slack directly from [agentr.dev](https://agentr.dev). Visit [agentr.dev/apps](https://agentr.dev/apps) and enable Slack.

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_slack/README.md](./src/universal_mcp_slack/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_slack/mcp.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_slack/mcp.py
   ```

## 📁 Project Structure

```text
.
├── src/
│   └── universal_mcp_slack/
│       ├── __init__.py       # Package initializer
│       ├── mcp.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! 🚀_
universal-mcp-dialpad 0.1.1
A Universal MCP Application: universal_mcp_dialpad
License: MIT
Requires Python: >=3.11

# Dialpad Universal MCP Server

This repository contains an implementation of an Dialpad Universal MCP (Model Context Protocol) server. It provides a standardized interface for interacting with Dialpad'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 Dialpad directly from [agentr.dev](https://agentr.dev). Visit [agentr.dev/apps](https://agentr.dev/apps) and enable Dialpad.

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_dialpad/README.md](./src/universal_mcp_dialpad/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_dialpad/mcp.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_dialpad/mcp.py
   ```

## 📁 Project Structure

```text
.
├── src/
│   └── universal_mcp_dialpad/
│       ├── __init__.py       # Package initializer
│       ├── mcp.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! 🚀_
universal-mcp-neon 0.1.1
A Universal MCP Application: universal_mcp_neon
License: MIT
Requires Python: >=3.11

# Neon Universal MCP Server

This repository contains an implementation of an Neon Universal MCP (Model Context Protocol) server. It provides a standardized interface for interacting with Neon'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 Neon directly from [agentr.dev](https://agentr.dev). Visit [agentr.dev/apps](https://agentr.dev/apps) and enable Neon.

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_neon/README.md](./src/universal_mcp_neon/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_neon/mcp.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_neon/mcp.py
   ```

## 📁 Project Structure

```text
.
├── src/
│   └── universal_mcp_neon/
│       ├── __init__.py       # Package initializer
│       ├── mcp.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! 🚀_
spmlab 0.1.5
Utility tools for reading, analyzing, and plotting scanning probe microscopy data.
License: MIT
Requires Python: <4.0,>=3.10
Keywords: stm, spym, sm4, scanning tunneling microscope, spm, microscopy

# spmlab

Utility tools for reading, analyzing, and plotting scanning probe microscopy data.

### Installation
```bash
pip install spmlab
```
dirmaptree 0.1.2
A clean directory tree generator with customizable exclusions and comments
License: MIT
Requires Python: >=3.11

# DirMapTree 🌳

A Python package for generating clean, customizable directory tree visualizations with:
- Built-in exclusion of common directories (`node_modules`, `.git`, etc.)
- Optional comments for important paths
- Hidden file visibility control
- Depth limiting
- Permission error handling

## Installation

```bash
pip install dirmaptree
Basic Usage
bash
dirmaptree [path] [-d DEPTH] [-H] [-c]
```
### Examples

1. Basic directory tree
```dirmaptree ./my-project```
Output:

```my-project/
├── src/
│   ├── app/
│   ├── components/
│   └── utils/
├── public/
│   └── assets/
├── pyproject.toml
└── README.md
```
2. With depth limit (2 levels)

```dirmaptree ./my-project -d 2```
3. Show hidden files

```dirmaptree ./my-project -H```
4. With comments

```dirmaptree ./my-project -c```
Output:
```
my-project/
├── src/app/                  # App Router (Next.js 13+)
├── src/components/           # Reusable UI components
├── public/assets/images/     # Product images
└── README.md
```
### Advanced Features

###### Custom Exclusions
Create a custom configuration file .dirmaptree in your project root:

```
exclude_dirs:
  - venv
  - dist
exclude_files:
  - *.log
  - *.tmp
comments:
  src/app: "App Router (Next.js 13+)"
  tests: "Test cases"
  
 ```
### Programmatic Usage

```
from dirmaptree import DirectoryTree

tree = DirectoryTree(
    exclude_dirs=['__pycache__', 'temp'],
    show_hidden=False
)
print(tree.generate('./my-project', max_depth=3))
```
### Command Line Options
|Option|	Description|
|------|---------------|
|[path] |	Root directory (default: current directory)|
| -d DEPTH, --depth | DEPTH	Maximum depth to display |
| -H, --hidden |	Show hidden files and directories |
| -c, --comments |	Show directory comments |
| --version	| Show version and exit |

### Configuration

##### DirMapTree automatically looks for these configuration files:

1. .dirmaptree (YAML format) in current directory

2. .dirmaptree in home directory

3. Package defaults
macrocosm-visual 0.1.4
Macrocosm Visual Engine
License: MIT

# Macrocosm Visual Engine

## Introduction
The package contains allows to setup Python's standard plotting libraries (`matplotlib`, `plotly`) to create visualizations that are consistent with the Macrocosm project's visual identity.

## Example

After installing the package, import the setup utils
```
from macrocosm_visual.viz_setup import setup_matplotlib, setup_plotly
```

Then, run the setup functions for the desired library. For example, for `matplotlib` run
```
setup_matplotlib()
```
The plots will now be styled according to the Macrocosm project's visual identity.

The `setup_matplotlib` and `setup_plotly` functions return a `VizSetup` object. This
object can be used to customize the visualizations further. `VizSetup` objects can be initialized
with any desired configuration - see `viz-configs-template.yaml` for an example configuration file.
See the docstrings for more information on `VizSetup`.