gqai

gqai

graphql → ai

gqai is a lightweight proxy that exposes GraphQL operations as Model Context Protocol (MCP) tools for AI models like ChatGPT. It lets you define tools using regular GraphQL queries/mutations and run them locally or expose them over HTTP.

🔌 Powered by your GraphQL backend ⚙️ Driven by .graphqlrc.yml + plain .graphql files 🧠 Model-ready inputs/outputs📍 Built in Go

✨ Features

• 🧰 Run GraphQL operations as tools via CLI
• 🌐 Serve tools via HTTP for AI agents
• 🗂 Automatically discover operations from .graphqlrc.yml
• 🧾 Tool metadata compatible with OpenAI function calling / MCP

🛠️ Installation

go install github.com/fotoetienne/gqai@latest

🚀 Quick Start

1. Create a .graphqlrc.yml:

schema: "https://graphql.org/graphql/"
documents: "operations"

This file tells gqai where to find your GraphQL schema and operations.

Note: The schema also tells gqai where to execute the operations. This must be a live server rather than a static schema file

2. Write a GraphQL operation (operations/getAllFilms.graphql):

query getAllFilms {
  allFilms {
    films {
      title
      episodeID
    }
  }
}

3. Run it via CLI:

gqai run getAllFilms

🌐 HTTP Server

Run a local server that exposes your tools via HTTP:

gqai serve

Call the tools via HTTP POST requests:

curl -X POST http://localhost:8080/tools/call  -d '{"toolName": "getAllFilms"}'

📦 Tool Metadata

Auto-generated tool specs for each operation, so you can plug into any LLM that supports tool use.

🤖 Why gqai?

gqai makes it easy to turn your GraphQL backend into a model-ready tool layer — no wrappers, no extra infra. Just define your operations and let AI call them.

🧪 Roadmap

• CLI tool runner

• HTTP server mode (gqai serve)

• Tool metadata generation

• JSON Schema validation

• Plug-and-play with OpenAI, Fireworks, etc.

📜 License

MIT — fork it, build on it, model all the things.

👋 Author

Made with ❤️ and 🤖vibes by Stephen Spalding