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Quadrant

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Enables document storage and semantic search with geospatial filtering using Qdrant, and coordinate conversion between TLC, Plasma, and addresses.

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Описание

Enables document storage and semantic search with geospatial filtering using Qdrant, and coordinate conversion between TLC, Plasma, and addresses.

README

A Model Context Protocol (MCP) server providing coordinate conversion tools and document search with Qdrant vector database, featuring quadrant-based spatial search and filtering.

🚀 Features

  • Document Storage: Store and retrieve document chunks with optional geolocation
  • Quadrant-Based Search: Search within specific geographic quadrants (NE, NW, SE, SW)
  • Location-Based Search: Find documents near specific coordinates
  • Hybrid Search: Combine semantic search with geospatial filtering
  • Fast Vector Search: Powered by Qdrant's efficient vector similarity search

🚀 Quick Start with UV

1. Install UV (if not already installed)

# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

# Or with pip
pip install uv

2. Setup the Project

# Navigate to your project directory
cd MCP_ADDRESS

# Create a virtual environment and install dependencies
uv venv
uv pip install -e .

3. Run the MCP Server

# Activate the virtual environment (optional, uv can run without activation)
# On macOS/Linux:
source .venv/bin/activate
# On Windows:
.venv\Scripts\activate

# Run
python -m uvicorn main:app --host 0.0.0.0 --port 8000 --reload

The server will start on http://127.0.0.1:8000/sse/

To run the MCP inspector

npx @modelcontextprotocol/inspector http://127.0.0.1:8000/sse/

🔧 Configure Claude Desktop

Add this to your Claude Desktop config file:

Location:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json

Configuration:

{
  "mcpServers": {
    "quadrant": {
      "command": "uv",
      "args": [
        "--directory",
        "/absolute/path/to/MCP_ADDRESS",
        "run",
        "python",
        "main.py"
      ]
    }
  }
}

Replace /absolute/path/to/MCP_QUADRANT with your actual project path.

📦 Available Tools

Coordinate Conversion

  1. tlc_to_address_tool - Convert TLC codes to addresses
  2. address_to_tlc_tool - Convert addresses to TLC codes
  3. address_to_plasma_tool - Convert addresses to Plasma format
  4. plasma_to_address_tool - Convert Plasma coordinates to addresses

Document Search & Storage

  1. store_document_chunks - Store document chunks with optional geolocation
  2. search_documents_by_quadrant - Search within a specific geographic quadrant
  3. search_documents_near_location - Search near specific coordinates
  4. search_documents_by_filename - Search documents by filename

from github.com/sakshi-rumsan/mcp_address

Установка Quadrant

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/sakshi-rumsan/mcp_address

FAQ

Quadrant MCP бесплатный?

Да, Quadrant MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Quadrant?

Нет, Quadrant работает без API-ключей и переменных окружения.

Quadrant — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Quadrant в Claude Desktop, Claude Code или Cursor?

Открой Quadrant на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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