https://github.com/fotoetienne/gqai
Turn any GraphQL endpoint into a set of MCP tools
https://github.com/fotoetienne/gqai
Last synced: about 2 months ago
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Turn any GraphQL endpoint into a set of MCP tools
- Host: GitHub
- URL: https://github.com/fotoetienne/gqai
- Owner: fotoetienne
- License: mit
- Created: 2025-04-14T21:38:36.000Z (2 months ago)
- Default Branch: main
- Last Pushed: 2025-04-17T06:02:56.000Z (2 months ago)
- Last Synced: 2025-04-17T17:21:03.968Z (2 months ago)
- Language: Go
- Size: 40 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- mcp-index - gqai - Expose GraphQL backend operations as callable tools for AI models, enabling seamless integration of GraphQL queries and mutations. Automatically generate an MCP server from GraphQL schemas and operations for AI invocation with or without arguments. (Content Creation)
- awesome-mcp-servers - fotoetienne/gqai - 通常の GraphQL クエリ/ミューテーション定義ツールを使用すると、gqai によって MCP サーバーが自動的に生成されます。 (サーバー実装 / 🛠️ <a name="other-tools-and-integrations"></a>その他のツールと統合)
README
# gqai
*graphql → ai*
**gqai** is a lightweight proxy that exposes GraphQL operations as
[Model Context Protocol (MCP)](https://platform.openai.com/docs/guides/function-calling) 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
```bash
go install github.com/fotoetienne/gqai@latest
```
## 🚀 Quick Start
1. Create a .graphqlrc.yml:
```yaml
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*
2. Add a GraphQL operation
`get_all_films.graphql`:
```graphql
# Get all Star Wars films
query get_all_films {
allFilms {
films {
title
episodeID
}
}
}
```
3. 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:
```bash
gqai tools/call get_all_films
```
This will execute the `get_all_films` tool and print the result.
```shell
{
"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`:
```graphql
query get_film_by_id($id: ID!) {
film(filmID: $id) {
episodeID
title
director
releaseDate
}
}
```
Call the tool with arguments:
```bash
gqai tools/call get_film_by_id '{"id": "1"}'
```
This will execute the `get_film_by_id` tool with the provided arguments.
```shell
{
"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 && ``