gqai

gqai

gqai

Category
Visit Server

README

gqai

graphql → ai

gqai is a lightweight proxy that exposes GraphQL operations as Model Context Protocol (MCP) tools for AI like Claude, Cursor, and ChatGPT.
Define tools using regular GraphQL queries/mutations against your GraphQL backend, and gqai automatically generates an MCP server for you.

🔌 Powered by your GraphQL backend
⚙️ Driven by .graphqlrc.yml + plain .graphql files


✨ Features

  • 🧰 Define tools using GraphQL operations
  • 🗂 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: .

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

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

  1. Add a GraphQL operation

get_all_films.graphql:

# Get all Star Wars films
query get_all_films {
  allFilms {
    films {
      title
      episodeID
    }
  }
}
  1. Add gqai to your mcp.json file:
  "gqai": {
    "command": "gqai",
    "args": [
      "run",
      "--config"
      ".graphqlrc.yml"
    ]
  }

That's it! Your AI model can now call the get_all_films tool.

🧪 CLI Testing

Call a tool via CLI to test:

gqai tools/call get_all_films

This will execute the get_all_films tool and print the result.

{
  "data": {
    "allFilms": {
      "films": [
        {
          "id": 4,
          "title": "A New Hope"
        },
        {
          "id": 5,
          "title": "The Empire Strikes Back"
        },
        {
          "id": 6,
          "title": "Return of the Jedi"
        },
        ...
      ]
    }
  }
}

Call a tool with arguments:

Create a GraphQL operation that takes arguments, and these will be the tool inputs:

get_film_by_id.graphql:

query get_film_by_id($id: ID!) {
  film(filmID: $id) {
    episodeID
    title
    director
    releaseDate
  }
}

Call the tool with arguments:

gqai tools/call get_film_by_id '{"id": "1"}'

This will execute the get_film_by_id tool with the provided arguments.

{
  "data": {
    "film": {
      "episodeID": 1,
      "title": "A New Hope",
      "director": "George Lucas",
      "releaseDate": "1977-05-25"
    }
  }
}

📦 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 code, no extra infra. Just define your operations and let AI call them.

📜 License

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

👋 Author

Made with ❤️ and 🤖vibes by Stephen Spalding && <your-name-here>

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured