semvec/pypi-packages huggingface dataset:
langsearch-mcp 0.1.1
Language-based search MCP server for semantic search and document reranking
License: MIT
Requires Python: >=3.10

# LangSearch MCP

A language-based search MCP server that provides semantic search and document reranking capabilities.

## Features

- Semantic web search
- Document reranking based on relevance
- Easy integration with MCP clients like Cherry Studio

## Installation

You can install the package using pip:

```bash
pip install langsearch-mcp
```

Or install from source:

```bash
git clone https://github.com/yourusername/langsearch-mcp
cd langsearch-mcp
pip install .
```

## Usage

### As a Command Line Tool

After installation, you can run the MCP server directly from the command line:

```bash
langsearch-mcp
```

### As an MCP Server

The server can be used with any MCP client, including Cherry Studio. The server provides the following endpoints:

- `web_search`: Perform semantic web search
- `rerank_documents`: Rerank documents based on relevance to a query

## Configuration

The server can be configured using environment variables:

- `PORT`: The port to run the server on (default: 8000)
- Add any other environment variables your server uses

## Development

To set up the development environment:

1. Clone the repository
2. Create a virtual environment: `python -m venv .venv`
3. Activate the virtual environment:
   - Windows: `.venv\Scripts\activate`
   - Unix/MacOS: `source .venv/bin/activate`
4. Install dependencies: `pip install -e ".[dev]"`

## License

MIT License