open-index/open-npm huggingface dataset:
npm package: @iflow-mcp/mcp-hello-world
Description: Simple hello world MCP server
Author: Moe03
Latest version: 0.1.0

# Google Maps MCP Server

MCP Server for the Google Maps API.

## Tools

1. `maps_geocode`
   - Convert address to coordinates
   - Input: `address` (string)
   - Returns: location, formatted_address, place_id

2. `maps_reverse_geocode`
   - Convert coordinates to address
   - Inputs:
     - `latitude` (number)
     - `longitude` (number)
   - Returns: formatted_address, place_id, address_components

3. `maps_search_places`
   - Search for places using text query
   - Inputs:
     - `query` (string)
     - `location` (optional): { latitude: number, longitude: number }
     - `radius` (optional): number (meters, max 50000)
   - Returns: array of places with names, addresses, locations

4. `maps_place_details`
   - Get detailed information about a place
   - Input: `place_id` (string)
   - Returns: name, address, contact info, ratings, reviews, opening hours

5. `maps_distance_matrix`
   - Calculate distances and times between points
   - Inputs:
     - `origins` (string[])
     - `destinations` (string[])
     - `mode` (optional): "driving" | "walking" | "bicycling" | "transit"
   - Returns: distances and durations matrix

6. `maps_elevation`
   - Get elevation data for locations
   - Input: `locations` (array of {latitude, longitude})
   - Returns: elevation data for each point

7. `maps_directions`
   - Get directions between points
   - Inputs:
     - `origin` (string)
     - `destination` (string)
     - `mode` (optional): "driving" | "walking" | "bicycling" | "transit"
   - Returns: route details with steps, distance, duration

## Setup

### API Key
Get a Google Maps API key by following the instructions [here](https://developers.google.com/maps/documentation/javascript/get-api-key#create-api-keys).

### Usage with Claude Desktop

Add the following to your `claude_desktop_config.json`:

#### Docker

```json
{
  "mcpServers": {
    "google-maps": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "GOOGLE_MAPS_API_KEY",
        "mcp/google-maps"
      ],
      "env": {
        "GOOGLE_MAPS_API_KEY": "<YOUR_API_KEY>"
      }
    }
  }
}
```

### NPX

```json
{
  "mcpServers": {
    "google-maps": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-google-maps"
      ],
      "env": {
        "GOOGLE_MAPS_API_KEY": "<YOUR_API_KEY>"
      }
    }
  }
}
```

## Build

Docker build:

```bash
docker build -t mcp/google-maps -f src/google-maps/Dockerfile .
```

## License

This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.
npm package: @iflow-mcp/mcp-image-compression
Description: [![MseeP.ai Security Assessment Badge](https://mseep.net/pr/inhiblabcore-mcp-image-compression-badge.png)](https://mseep.ai/app/inhiblabcore-mcp-image-compression)
Author: NelsonYong
Latest version: 0.1.2

[![MseeP.ai Security Assessment Badge](https://mseep.net/pr/inhiblabcore-mcp-image-compression-badge.png)](https://mseep.ai/app/inhiblabcore-mcp-image-compression)

# mcp-image-compression

## Project Overview

mcp-image-compression is a high-performance image compression microservice based on MCP (Modal Context Protocol) architecture. This service focuses on providing fast and high-quality image compression capabilities to help developers optimize image resources for websites and applications, improving loading speed and user experience.

## Features

- **Multi-format support**: Compress mainstream image formats including JPEG, PNG, WebP, AVIF
- **Offline Usage**: No need to connect to the internet to use
- **Smart compression**: Automatically select optimal compression parameters based on image content
- **Batch processing**: Support parallel compression of multiple images for improved efficiency
- **Quality control**: Customizable compression quality to balance file size and visual quality

## TOOLS

1. `image_compression`
   - Image compression
   - Inputs:
     - `urls` (strings): URLs of images to compress
     - `quality` (int): Quality of compression (0-100)
     - `format` (string): Format of compressed image (e.g. "jpeg", "png", "webp", "avif")
   - Returns: Compressed images url

## Setup

### NPX

```json
{
  "mcpServers": {
    "Image compression": {
      "command": "npx",
      "args": [
        "-y",
        "@inhiblab-core/mcp-image-compression"
      ],
      "env": {
        "IMAGE_COMPRESSION_DOWNLOAD_DIR": "<YOUR_DIR>"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}
```

## Build

```bash
docker build -t mcp-image-compression .
```

## License

This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.
npm package: @iflow-mcp/mcp-image-downloader
Description: MCP server for downloading and optimizing images
Author: qpd-v
Latest version: 0.1.0

# MCP Image Downloader

An MCP server that provides tools for downloading and optimizing images. Built using the Model Context Protocol (MCP), this server enables AI assistants to download images from URLs and perform basic image optimization tasks.

## Features

- Download images from URLs with proper error handling
- Optimize images with options for:
  - Resizing (maintaining aspect ratio)
  - Quality adjustment (JPEG/WebP)
  - Format conversion

## Installation

```bash
# Clone the repository
git clone https://github.com/qpd-v/mcp-image-downloader.git
cd mcp-image-downloader

# Install dependencies
npm install

# Build the project
npm run build
```

## Usage

### As an MCP Server

Add the server to your MCP configuration (e.g., in Claude Desktop's config):

```json
{
  "mcpServers": {
    "image-downloader": {
      "command": "node",
      "args": ["/path/to/mcp-image-downloader/build/index.js"]
    }
  }
}
```

### Available Tools

#### download_image
Downloads an image from a URL to a specified path.

Parameters:
- `url`: URL of the image to download
- `outputPath`: Path where to save the image

#### optimize_image
Creates an optimized version of an image.

Parameters:
- `inputPath`: Path to the input image
- `outputPath`: Path where to save the optimized image
- `width` (optional): Target width (maintains aspect ratio if only width is specified)
- `height` (optional): Target height (maintains aspect ratio if only height is specified)
- `quality` (optional): JPEG/WebP quality (1-100)

## Development

```bash
# Run in development mode
npm run start

# Build the project
npm run build
```

## Requirements

- Node.js 16 or higher
- NPM or compatible package manager

## License

MIT License - see the [LICENSE](LICENSE) file for details.

## Author

qpd-v

## Version

0.1.0 - Initial release
npm package: @iflow-mcp/mcp-installer
Description: A MCP server to install other MCP servers
Author: Ani Betts
Latest version: 0.5.0

# mcp-installer - A MCP Server to install MCP Servers

This server is a server that installs other MCP servers for you. Install it, and you can ask Claude to install MCP servers hosted in npm or PyPi for you. Requires `npx` and `uv` to be installed for node and Python servers respectively.

![image](https://github.com/user-attachments/assets/d082e614-b4bc-485c-a7c5-f80680348793)

### How to install:

Put this into your `claude_desktop_config.json` (either at `~/Library/Application Support/Claude` on macOS or `C:\Users\NAME\AppData\Roaming\Claude` on Windows):

```json
  "mcpServers": {
    "mcp-installer": {
      "command": "npx",
      "args": [
        "@anaisbetts/mcp-installer"
      ]
    }
  }
```

### Example prompts

> Hey Claude, install the MCP server named mcp-server-fetch

> Hey Claude, install the @modelcontextprotocol/server-filesystem package as an MCP server. Use ['/Users/anibetts/Desktop'] for the arguments

> Hi Claude, please install the MCP server at /Users/anibetts/code/mcp-youtube, I'm too lazy to do it myself.

> Install the server @modelcontextprotocol/server-github. Set the environment variable GITHUB_PERSONAL_ACCESS_TOKEN to '1234567890'
npm package: @iflow-mcp/mcp-intercom
Description: MCP server for Intercom chat integration
Latest version: 1.0.0

# MCP Intercom Server

A Model Context Protocol (MCP) server that provides access to Intercom conversations and chats. This server allows LLMs to query and analyze your Intercom conversations with various filtering options.

## Features

- Query Intercom conversations with filtering options:
  - Date range (start and end dates)
  - Customer ID
  - Conversation state
- Secure access using your Intercom API key
- Rich conversation data including:
  - Basic conversation details
  - Contact information
  - Statistics (responses, reopens)
  - State and priority information

## Installation

1. Clone the repository:
```bash
git clone https://github.com/fabian1710/mcp-intercom.git
cd mcp-intercom
```

2. Install dependencies:
```bash
npm install
```

3. Set up your environment:
```bash
cp .env.example .env
```

4. Add your Intercom API key to `.env`:
```
INTERCOM_API_KEY=your_api_key_here
```

5. Build the server:
```bash
npm run build
```

## Usage

### Running the Server

Start the server:
```bash
npm start
```

### Using with Claude for Desktop

1. Add the server to your Claude for Desktop configuration (`~/Library/Application Support/Claude/claude_desktop_config.json` on macOS or `%AppData%\Claude\claude_desktop_config.json` on Windows):

```json
{
  "mcpServers": {
    "intercom": {
      "command": "node",
      "args": ["/path/to/mcp-intercom/dist/index.js"],
      "env": {
        "INTERCOM_API_KEY": "your_api_key_here"
      }
    }
  }
}
```

2. Restart Claude for Desktop

### Available Tools

#### search-conversations

Searches Intercom conversations with optional filters.

Parameters:
- `createdAt` (optional): Object with `operator` (e.g., ">", "<", "=") and `value` (UNIX timestamp) for filtering by creation date.
- `updatedAt` (optional): Object with `operator` (e.g., ">", "<", "=") and `value` (UNIX timestamp) for filtering by update date.
- `sourceType` (optional): Source type of the conversation (e.g., "email", "chat").
- `state` (optional): Conversation state to filter by (e.g., "open", "closed").
- `open` (optional): Boolean to filter by open status.
- `read` (optional): Boolean to filter by read status.

Example queries:
- "Search for all conversations created after January 1, 2024"
- "Find conversations updated before last week"
- "List all open email conversations"
- "Get all unread conversations"

## Security

- The server requires an Intercom API key to function
- API key should be stored securely in environment variables
- The server only provides read access to conversations
- All API requests are made with proper authentication

## Development

1. Start development mode with auto-recompilation:
```bash
npm run dev
```

2. Run linting:
```bash
npm run lint
```

## Contributing

1. Fork the repository
2. Create a new branch for your feature
3. Make your changes
4. Submit a pull request

## License

MIT