Overview of gqai

gqai is a lightweight proxy that bridges GraphQL backends and AI assistants through the Model Context Protocol (MCP). By exposing GraphQL queries, mutations, and subscriptions as MCP tools, it eliminates the need for custom wrappers or SDKs when integrating AI models such as Claude, Cursor, or ChatGPT with existing GraphQL services. The core problem it solves is the friction developers face when turning a complex GraphQL schema into an actionable API for conversational agents. Instead of manually crafting function definitions, gqai automatically generates the necessary MCP metadata from your GraphQL schema and operation files.

At its heart, gqai operates as a command‑line tool that reads a standard configuration. This file declares the live GraphQL endpoint, document locations, and optional headers for authentication or custom routing. Once started, the server scans all files in the specified directories, extracts operation names and input types, and publishes them as MCP tools. Each tool is annotated with descriptive titles and parameter schemas that match the GraphQL operation’s arguments, ensuring seamless compatibility with OpenAI function calling and other MCP‑compliant assistants.

Key capabilities include:

• Zero‑code tool discovery – No boilerplate; simply add or modify GraphQL files and restart the server.
• Header injection with environment variable support – Securely pass tokens or API keys without hard‑coding them.
• Schema‑driven metadata – Tool definitions mirror the GraphQL schema, preserving type safety and reducing errors.
• Cross‑platform compatibility – Works with any MCP client, from OpenAI’s ChatGPT to Claude and Cursor.

Typical use cases span a wide range of real‑world scenarios. A product manager might ask an AI assistant to list all available products; the assistant calls the GraphQL query via gqai, and the response is returned in natural language. A developer could let an AI generate a mutation to create a new user, with gqai handling the underlying GraphQL call and validation. In customer support bots, gqai can expose ticket‑management queries, allowing agents to retrieve and update tickets without leaving the conversation.

Integrating gqai into an AI workflow is straightforward: add a single entry to your that launches the gqai binary with the appropriate configuration. The AI client then sees a catalog of tools that correspond directly to your GraphQL operations, enabling rich, typed interactions without additional development overhead. Its unique advantage lies in the declarative nature of GraphQL combined with MCP’s conversational interface, providing a powerful, low‑maintenance bridge between structured data services and intelligent agents.