semvec/pypi-packages huggingface dataset:
swinging-door 2.0.1
Implementation of the Swinging Door algorithm in Python.
Requires Python: >=3.9
Keywords: SwingingDoor

|License| |Release| |Supported versions| |Docs|
|Code Coverage| |Build status Appveyor| |Build Status Travis CI|
|Contact| |Blog|

Swinging Door
=============

Implementation of the Swinging Door algorithm in Python.

Example of usage
----------------

.. code:: python

    >>> from datetime import datetime
    >>> from pandas import read_csv, DataFrame

    >>> df = DataFrame(
    ...     [
    ...         {
    ...             "Date": datetime.strptime(date, "%Y-%m-%d"),
    ...             "Price": value
    ...         }
    ...         for date, value in read_csv(
    ...             "https://datahub.io/core/oil-prices/r/wti-daily.csv"
    ...         ).values.tolist()
    ...     ]
    ... )

    >>> print(len(df))
    9895

    >>> df.plot(x="Date", y="Price")

.. code:: python

    >>> from swinging_door import swinging_door

    >>> compress = DataFrame(
    ...      list(
    ...         {
    ...             "Date": datetime.fromtimestamp(date),
    ...             "Price": value
    ...         }
    ...         for date, value in swinging_door(
    ...             iter(
    ...                 (date.timestamp(), value)
    ...                 for date, value in df.values.tolist()
    ...             ), deviation=.5
    ...         )
    ...     )
    ... )

    >>> print(len(compress))
    3392

    >>> compress.plot(x="Date", y="Price")

.. |License| image:: https://img.shields.io/badge/License-MIT-yellow.svg
   :target:  https://opensource.org/licenses/MIT
.. |Release| image:: https://img.shields.io/github/release/chelaxe/SwingingDoor.svg
   :target: https://github.com/chelaxe/SwingingDoor/releases
.. |Supported versions| image:: https://img.shields.io/pypi/pyversions/swinging_door.svg
   :target: https://pypi.org/project/swinging_door/
.. |Docs| image:: https://readthedocs.org/projects/swingingdoor/badge/?version=latest&style=flat
   :target:  https://swingingdoor.readthedocs.io/en/latest/
.. |Code Coverage| image:: https://codecov.io/gh/chelaxe/SwingingDoor/branch/main/graph/badge.svg
   :target: https://codecov.io/gh/chelaxe/SwingingDoor
.. |Build status Appveyor| image:: https://ci.appveyor.com/api/projects/status/github/chelaxe/swingingdoor?branch=main&svg=true
   :target: https://ci.appveyor.com/project/chelaxe/swingingdoor
.. |Build Status Travis CI| image:: https://api.travis-ci.com/chelaxe/SwingingDoor.svg?branch=main
   :target: https://app.travis-ci.com/github/chelaxe/SwingingDoor
.. |Contact| image:: https://img.shields.io/badge/telegram-write%20me-blue.svg
   :target:  https://t.me/chelaxe
.. |Blog| image:: https://img.shields.io/badge/site-my%20blog-yellow.svg
   :target:  https://chelaxe.ru/
mcp-amadeus 0.0.2
MCP server for Amadeus integration
Requires Python: >=3.10

# Amadeus MCP Server

A Model Context Protocol (MCP) server for Amadeus API integration. This server provides tools for interacting with Amadeus travel-related services, including flight search, hotel booking, and airport information.

## Features

- **Flight Search**: Search for available flights between destinations
- **Hotel Booking**: Find accommodations in specific cities
- **Airport & City Information**: Get details about airports and cities
- **Travel Planning Assistance**: Prompts for common travel workflows

## Installation

```bash
pip install mcp-amadeus
```

## Configuration

Set the following environment variables:

```bash
export AMADEUS_CLIENT_ID="your_client_id"
export AMADEUS_CLIENT_SECRET="your_client_secret"
export AMADEUS_BASE_URL="https://test.api.amadeus.com/v1"  # Use test or production URL
```

## Usage

### Starting the server directly

```bash
mcp-amadeus
```

### Using with Claude Desktop

Add the following to your `claude_desktop_config.json` file:

```json
"mcp-amadeus": {
  "command": "uvx",
  "args": [
    "mcp-amadeus"
  ],
  "env": {
    "AMADEUS_CLIENT_ID": "your_client_id",
    "AMADEUS_CLIENT_SECRET": "your_client_secret",
    "AMADEUS_BASE_URL": "https://test.api.amadeus.com/v1"
  }
}
```

Replace the environment variables with your actual Amadeus API credentials.

## Available Tools

* **search_flights**: Search for flight options between destinations
* **search_hotels**: Search for hotel options in a city
* **get_airport_info**: Get information about an airport by its IATA code
* **get_city_info**: Get information about a city by its IATA code
* **get_flight_offers_price**: Get pricing for specific flight offers

## Available Resources

* **amadeus://airports**: List of popular airports
* **amadeus://cities**: List of popular cities

## Available Prompts

* **plan_trip**: Template for planning a complete trip with flights and accommodations
* **find_flight**: Template for finding a flight between two locations
* **find_hotel**: Template for finding accommodations in a specific location

## Authentication

This MCP server implements OAuth 2.0 authentication with the Amadeus API using client credentials. The token is automatically managed and refreshed as needed.

## Error Handling

The server includes robust error handling for:
- API authentication failures
- Invalid requests
- Server errors
- Network issues

## Version

0.0.1

## License

MIT
mcp-elevenlabs 0.0.2
MCP server for Elevenlabs integration
Requires Python: >=3.10

# Elevenlabs MCP Server

A Model Context Protocol (MCP) server for Elevenlabs integration. This server provides tools for interacting with Elevenlabs' text-to-speech API, allowing you to generate realistic speech from text, access voice libraries, and manage your account.

## Features

- **Text-to-Speech**: Convert text to high-quality speech
- **Voice Management**: List and get details about available voices
- **Model Selection**: Access different TTS models for various use cases
- **User Management**: Check subscription status and usage limits
- **History Tracking**: View your generation history
- **Resources**: Access metadata about Elevenlabs objects
- **Prompts**: Templates for common Elevenlabs workflows

## Installation

```bash
pip install mcp-elevenlabs
```

## Configuration

Set the following environment variables:

```bash
export ELEVENLABS_API_KEY="your_api_key"
export ELEVENLABS_BASE_URL="https://api.elevenlabs.io/v1" # Optional, defaults to this value
```

## Usage

### Starting the server directly

```bash
mcp-elevenlabs
```

### Using with Claude Desktop

Add the following to your `claude_desktop_config.json` file:

```json
{
  "mcpServers": {
    "mcp-elevenlabs": {
      "command": "uvx",
      "args": [
        "mcp-elevenlabs"
      ],
      "env": {
        "ELEVENLABS_API_KEY": "your_api_key_here"
      }
    }
  }
}
```

Replace the environment variables with your actual Elevenlabs credentials.

## Available Tools

* **text_to_speech**: Convert text to speech using Elevenlabs API
* **get_voices**: Get a list of available voices
* **get_voice**: Get details of a specific voice
* **get_models**: Get a list of available TTS models
* **get_user_info**: Get information about the current user's subscription
* **get_history**: Get the user's text-to-speech generation history

## Available Resources

* **elevenlabs://voices**: List of all Elevenlabs voices
* **elevenlabs://models**: List of all available TTS models
* **elevenlabs://user**: User subscription information
* **elevenlabs://history**: Generation history

## Available Prompts

* **tts_generation**: Template for generating text-to-speech
* **voice_selection**: Guide for selecting the right voice

## Example Usage

Once connected to Claude, you can use the Elevenlabs MCP server to generate speech:

```
Convert this text to speech: "Hello, world! This is a test of the Elevenlabs text-to-speech system."
```

Claude will use the text_to_speech tool to generate speech from your text.

To get information about available voices:

```
What voices are available in Elevenlabs?
```

Claude will use the get_voices tool to retrieve and display the list of voices.

## Version

0.0.1
mcp-figma 0.0.2
MCP server for Figma integration
Requires Python: >=3.10

# Figma MCP Server

A Model Context Protocol (MCP) server for Figma integration. This server provides tools for interacting with Figma, including querying files, comments, projects, and performing operations.

## Features

- **File Access**: Get file information, version history, and export files
- **Comments**: Create, read, and manage comments on designs
- **Team Management**: Access teams, projects, and file permissions
- **Component Libraries**: Access and query component libraries
- **Resources**: Access metadata about Figma objects
- **Prompts**: Templates for common Figma workflows

## Installation

```bash
pip install mcp-figma
```

## Configuration

Set the following environment variables:

```bash
export FIGMA_BASE_URL="https://api.figma.com/v1"
export FIGMA_ACCESS_TOKEN="your_figma_personal_access_token"
```

You can generate a personal access token in Figma by going to Account Settings > Personal Access Tokens.

## Usage

### Starting the server directly

```bash
mcp-figma
```

### Using with Claude Desktop

Add the following to your `claude_desktop_config.json` file:

```json
{
  "mcpServers": {
    "mcp-figma": {
      "command": "uvx",
      "args": [
        "mcp-figma"
      ],
      "env": {
        "FIGMA_BASE_URL": "https://api.figma.com/v1",
        "FIGMA_ACCESS_TOKEN": "your_figma_personal_access_token"
      }
    }
  }
}
```

Replace the environment variables with your actual Figma credentials.

## Available Tools

* **get_file**: Get details of a specific Figma file
* **get_file_nodes**: Get specific nodes from a Figma file
* **get_comments**: Get comments from a Figma file
* **create_comment**: Create a comment on a Figma file
* **get_file_versions**: Get version history of a Figma file
* **get_team_projects**: Get projects for a Figma team
* **get_project_files**: Get files in a Figma project
* **export_image**: Export parts of a Figma document as images

## Available Resources

* **figma://files**: List of recently accessed Figma files
* **figma://teams**: List of Figma teams you belong to
* **figma://components**: List of components in a file
* **figma://styles**: List of styles in a file or team library

## Available Prompts

* **create_comment_prompt**: Template for creating a new comment
* **analyze_design_prompt**: Template for analyzing a design file
* **export_assets_prompt**: Template for exporting assets from a design

## Version

0.0.1
mcp-mixpanel 0.0.2
MCP server for Mixpanel integration
Requires Python: >=3.10

# Mixpanel MCP Server

A Model Context Protocol (MCP) server for Mixpanel integration. This server provides tools for interacting with Mixpanel, including querying events, analyzing funnels, working with user profiles, and managing annotations.

## Features

- **Event Analysis**: Query and analyze Mixpanel event data
- **User Profiles**: Retrieve and examine user profile information
- **Funnels**: Analyze conversion funnels for user journeys
- **Cohorts**: Work with user cohorts
- **Annotations**: Create and manage annotations to mark important events
- **Data Export**: Export raw event data for external analysis

## Installation

```bash
pip install mcp-mixpanel
```

## Configuration

Set the following environment variables:

```bash
export MIXPANEL_API_SECRET="your_api_secret"
export MIXPANEL_PROJECT_ID="your_project_id"  # Optional
export MIXPANEL_SERVICE_ACCOUNT_USERNAME="username"  # Optional alternative auth
export MIXPANEL_SERVICE_ACCOUNT_PASSWORD="password"  # Optional alternative auth
```

## Usage

### Starting the server directly

```bash
mcp-mixpanel
```

### Using with Claude Desktop

Add the following to your `claude_desktop_config.json` file:

```json
"mcp-mixpanel": {
  "command": "uvx",
  "args": [
    "mcp-mixpanel"
  ],
  "env": {
    "MIXPANEL_API_SECRET": "your_api_secret",
    "MIXPANEL_PROJECT_ID": "your_project_id"
  }
}
```

Replace the environment variables with your actual Mixpanel credentials.

## Available Tools

* **query_events**: Query Mixpanel events by name, date range, and other parameters
* **get_user_profile**: Retrieve detailed profile information for a specific user
* **create_annotation**: Create an annotation to mark important events or changes
* **get_funnel_data**: Analyze conversion data for a specific funnel
* **get_cohorts**: List all cohorts defined in your Mixpanel project
* **export_events**: Export raw event data for external analysis

## Available Resources

* **mixpanel://events**: List of all event names in your Mixpanel project
* **mixpanel://properties**: List of all event properties in your Mixpanel project
* **mixpanel://funnels**: List of all funnels in your Mixpanel project
* **mixpanel://annotations**: List of all annotations in your Mixpanel project

## Available Prompts

* **query_events**: Template for querying and analyzing event data
* **funnel_analysis**: Template for analyzing funnel performance
* **create_annotation**: Template for creating annotations for important events

## Version

0.0.1
mcp-notion 0.0.2
MCP server for Notion integration
Requires Python: >=3.10

# Notion MCP Server

A Model Context Protocol (MCP) server for Notion integration. This server provides tools for interacting with Notion, including querying pages, databases, and blocks.

## Features

- **Page Management**: Get, create, and update Notion pages
- **Database Operations**: Query, filter, and sort Notion databases
- **Block Operations**: Get and append blocks to pages
- **Search**: Query for Notion content
- **Resources**: Access metadata about Notion objects
- **Prompts**: Templates for common Notion workflows

## Installation

```bash
pip install mcp-notion
```

## Configuration

Set the following environment variables:

```bash
export NOTION_API_KEY="your_notion_integration_token"
export NOTION_VERSION="2022-06-28"  # Optional, will use default if not specified
```

You can get your Notion API key by creating an integration at https://www.notion.so/my-integrations

## Usage

### Starting the server directly

```bash
mcp-notion
```

### Using with uvx

```bash
uvx mcp-notion
```

### Using with Claude Desktop

Add the following to your `claude_desktop_config.json` file:

```json
"mcp-notion": {
  "command": "uvx",
  "args": [
    "mcp-notion"
  ],
  "env": {
    "NOTION_API_KEY": "your_notion_integration_token",
    "NOTION_VERSION": "2022-06-28"
  }
}
```

Replace the environment variables with your actual Notion credentials.

## Available Tools

* **search_notion**: Search Notion content with optional filters
* **get_page**: Get details of a specific Notion page
* **get_block_children**: Get children blocks of a block or page
* **get_database**: Get details of a specific Notion database
* **query_database**: Query a Notion database with optional filters and sorting
* **create_page**: Create a new page in a database or as a child of another page
* **update_page**: Update properties of an existing Notion page
* **append_blocks**: Append new blocks to an existing block or page

## Available Resources

* **notion://search**: Search all Notion content
* **notion://databases**: List of all Notion databases the user has access to
* **notion://users**: List of all users in the workspace

## Available Prompts

* **create_database_entry**: Template for creating a new entry in a database
* **search_and_summarize**: Template for searching and summarizing Notion content
* **database_query_builder**: Template for building Notion database queries

## Notes on Authentication

1. You need to create a Notion integration at https://www.notion.so/my-integrations
2. You must share specific pages/databases with your integration
3. Make sure your integration has the appropriate capabilities (Read, Update, etc.)

## Version

0.0.1
mcp-slack 0.0.2
MCP server for Slack integration
Requires Python: >=3.10

# Slack MCP Server

A Model Context Protocol (MCP) server for Slack integration. This server provides tools for interacting with Slack, including sending messages, managing channels, and accessing workspace information.

## Features

- **Channel Management**: Create, list, join, and archive channels
- **Messaging**: Send messages to channels or threads, get channel history
- **Users**: Get user information and list workspace members
- **Files**: Upload files to channels
- **Reactions**: Add reactions to messages
- **Resources**: Access information about channels, users, and messages
- **Prompts**: Templates for common Slack actions

## Installation

```bash
pip install mcp-slack
```

## Configuration

Set the following environment variables:

```bash
export SLACK_BOT_TOKEN="xoxb-your-bot-token"
export SLACK_APP_TOKEN="xapp-your-app-token" # Optional, needed for socket mode
```

To get these tokens:
1. Create a Slack App at https://api.slack.com/apps
2. Add the necessary permission scopes (channels:read, chat:write, etc.)
3. Install the app to your workspace
4. Get the Bot Token from the "OAuth & Permissions" page

## Usage

### Starting the server directly

```bash
mcp-slack
```

### Using with Claude Desktop

Add the following to your `claude_desktop_config.json` file:

```json
"mcp-slack": {
  "command": "uvx",
  "args": [
    "mcp-slack"
  ],
  "env": {
    "SLACK_BOT_TOKEN": "xoxb-your-bot-token",
    "SLACK_APP_TOKEN": "xapp-your-app-token"
  }
}
```

Replace the environment variables with your actual Slack credentials.

## Available Tools

* **send_message**: Send a message to a channel or thread
* **list_channels**: List available channels in the workspace
* **get_channel_history**: Get message history for a channel
* **list_users**: List users in the workspace
* **create_channel**: Create a new channel
* **archive_channel**: Archive a channel
* **join_channel**: Join a channel
* **add_reaction**: Add a reaction to a message
* **upload_file**: Upload a file to a channel

## Available Resources

* **slack://channels**: List of all channels in the workspace
* **slack://users**: List of all users in the workspace
* **slack://channel/{channel_id}**: Information about a specific channel
* **slack://user/{user_id}**: Information about a specific user

## Available Prompts

* **create_message**: Template for creating a new message
* **create_channel**: Template for creating a new channel
* **schedule_message**: Template for scheduling a message

## Permissions Required

The Slack bot requires the following scopes:
* `channels:read` - To list and get channel information
* `channels:write` - To create and archive channels
* `chat:write` - To send messages
* `files:write` - To upload files
* `reactions:write` - To add reactions
* `users:read` - To list and get user information

## Version

0.0.1
mcp-twitter 0.0.2
MCP server for Twitter integration
Requires Python: >=3.10

# Twitter MCP Server

A Model Context Protocol (MCP) server for Twitter integration. This server provides tools for interacting with Twitter, including searching tweets, retrieving user profiles, posting tweets, and analyzing trends.

## Features

- **User Management**: Get user profiles and details
- **Tweet Operations**: Post, read, and search tweets
- **Trends Analysis**: Discover and analyze trending topics
- **Resources**: Access Twitter data through URI templates
- **Prompts**: Templates for common Twitter workflows

## Installation

```bash
pip install mcp-twitter
```

## Configuration

Set the following environment variables:

```bash
# Required for read-only operations (Bearer Token authentication)
export TWITTER_BEARER_TOKEN="your_bearer_token"

# Required for write operations (OAuth 1.0a)
export TWITTER_API_KEY="your_api_key"
export TWITTER_API_SECRET="your_api_secret"
export TWITTER_ACCESS_TOKEN="your_access_token"
export TWITTER_ACCESS_SECRET="your_access_secret"

# Optional - change API base URL if needed
export TWITTER_BASE_URL="https://api.twitter.com/2"
```

## Usage

### Starting the server directly

```bash
mcp-twitter
```

### Using with Claude Desktop

Add the following to your `claude_desktop_config.json` file:

```json
"mcp-twitter": {
  "command": "uvx",
  "args": [
    "mcp-twitter"
  ],
  "env": {
    "TWITTER_BEARER_TOKEN": "your_bearer_token",
    "TWITTER_API_KEY": "your_api_key",
    "TWITTER_API_SECRET": "your_api_secret",
    "TWITTER_ACCESS_TOKEN": "your_access_token",
    "TWITTER_ACCESS_SECRET": "your_access_secret"
  }
}
```

Replace the environment variables with your actual Twitter API credentials.

## Available Tools

* **get_user**: Get details of a specific Twitter user by username
* **get_tweet**: Get details of a specific tweet by ID
* **search_tweets**: Search for tweets matching a query
* **get_user_tweets**: Get recent tweets from a specific user
* **get_trending_topics**: Get trending topics on Twitter
* **post_tweet**: Post a new tweet (requires OAuth 1.0a credentials)

## Available Resources

* **twitter://user/{username}**: Get details about a Twitter user
* **twitter://tweets/user/{username}**: Get recent tweets from a specific user
* **twitter://trends**: Get current trending topics on Twitter

## Available Prompts

* **draft_tweet**: Template for drafting a tweet on a specific topic
* **analyze_trends**: Template for analyzing Twitter trends
* **engagement_strategy**: Template for developing a Twitter engagement strategy

## Getting Twitter API Credentials

1. Create a Twitter Developer account at [developer.twitter.com](https://developer.twitter.com/)
2. Create a new project and app
3. Generate the necessary keys and tokens:
   - For read-only access: Bearer Token
   - For write access: Consumer Keys (API Key & Secret) and Authentication Tokens (Access Token & Secret)

## Version

0.0.1