MCP(Model Context Protocol) 서버를 사용하여 GraphQL 쿼리에 자연적인 언어 쿼리를 전달하여 Claude Desktop 및 Cursor와 같은 AI 조수와 원활하게 통합합니다.

🚀 개요

텍스트에 그래프QL MCP Server는 LangGraph와 내장 된 AI 에이전트를 사용하여 유효한 GraphQL 쿼리에 자연 언어 설명을 변환합니다. 그것은 인간의 언어와 GraphQL API 사이의 브리지를 제공, 데이터베이스와 API 상호 작용을 더 직관적인 개발자와 비 기술적인 사용자를 위해.

✨ 특징

-Natural Language to GraphQL: 유효한 GraphQL에 일반 영어 쿼리를 변환

• ** 화학 관리 **: Load and introspect GraphQL 스키마는 자동으로
• ** 쿼리 검증**: loaded schemas에 대한 생성 된 쿼리
• ** 쿼리 실행 **: GraphQL 엔드포인트에 대한 쿼리 수행 -Query History: 세션을 통해 쿼리의 역사를 추적하고 관리
• MCP Protocol: Claude Desktop, Cursor 및 기타 MCP 클라이언트와의 완벽한 호환성
• 처리: 상세한 디버깅 정보로 Graceful error handling -Caching: schemas 및 자주 사용되는 쿼리에 대한 내장 캐싱

 임명

Text-to-GraphQL MCP Server

Transform natural language queries into GraphQL queries using an MCP (Model Context Protocol) server that integrates seamlessly with AI assistants like Claude Desktop and Cursor.

🚀 Overview

The Text-to-GraphQL MCP Server converts natural language descriptions into valid GraphQL queries using an AI agent built with LangGraph. It provides a bridge between human language and GraphQL APIs, making database and API interactions more intuitive for developers and non-technical users alike.

✨ Features

• Natural Language to GraphQL: Convert plain English queries to valid GraphQL
• Schema Management: Load and introspect GraphQL schemas automatically
• Query Validation: Validate generated queries against loaded schemas
• Query Execution: Execute queries against GraphQL endpoints with authentication
• Query History: Track and manage query history across sessions
• MCP Protocol: Full compatibility with Claude Desktop, Cursor, and other MCP clients
• Error Handling: Graceful error handling with detailed debugging information
• Caching: Built-in caching for schemas and frequently used queries

🛠 Installation

Prerequisites: Install UV (Recommended)

UV is a fast Python package installer and resolver. Install it first:

macOS/Linux:

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

Windows:

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

Find your UV installation path:

# Find where uv is installed
which uv

# Common locations:
# macOS/Linux: ~/.local/bin/uv
# Windows: %APPDATA%\uv\bin\uv.exe

Important: You’ll need the UV path for MCP configuration. The typical path is ~/.local/bin on macOS/Linux, which translates to /Users/yourusername/.local/bin (replace yourusername with your actual username).

Setup for MCP Usage

# Clone the repository
git clone https://github.com/Arize-ai/text-to-graphql-mcp.git
cd text-to-graphql-mcp

# Install dependencies (UV automatically creates virtual environment)
uv sync

# Test the installation
uv run text-to-graphql-mcp --help

Note: The uv run pattern automatically handles virtual environments, making MCP configuration cleaner and more reliable than traditional pip installations.

Alternative Installation Methods

From PyPI (when published):