MCP GraphQL

GraphQL MCP Server

The GraphQL MCP server bridges the gap between AI assistants and GraphQL APIs by exposing every query in a schema as an autonomous MCP tool. Instead of writing custom adapters for each endpoint, developers can simply point the server at a GraphQL endpoint and immediately obtain a ready‑to‑use set of tools that mirror the API’s capabilities. This eliminates boilerplate and reduces friction when integrating complex data services into conversational agents.

By introspecting the GraphQL schema, the server auto‑generates JSON schemas for tool inputs that match query parameters exactly. This means the assistant receives strongly typed prompts, ensuring correct field names and value types without manual intervention. The tool’s output is returned as JSON, allowing downstream processing or transformation by other MCP tools in a seamless pipeline. For developers, this translates to faster prototyping and fewer runtime errors when working with nested or polymorphic GraphQL types.

Key capabilities include:

• Zero‑configuration schema exposure – just provide the API URL and optional credentials, and all available queries become tools.
• Dynamic input validation – automatically generated JSON schemas prevent malformed requests.
• Configurable authentication – support for Bearer, Basic, or custom headers lets the server adapt to any security model.
• Automatic query generation – when no explicit queries are supplied, the server builds a breadth‑first request up to a configurable depth, ideal for exploratory testing.
• Future mutation support – the architecture is primed to expose mutations once released, expanding the server’s utility beyond read‑only operations.

Typical use cases involve:

• Chatbot data retrieval – an AI assistant can fetch user profiles, product listings, or analytics dashboards by invoking the corresponding tool.
• Dynamic form generation – tools can supply schema definitions that front‑end clients consume to build UI components on the fly.
• Data enrichment pipelines – multiple GraphQL tools can be chained in an MCP workflow to aggregate, transform, and store information across services.

Integrating the server into AI workflows is straightforward: after launching it with a single command, any MCP‑compatible client automatically discovers the available tools via the standard protocol discovery endpoint. The assistant can then prompt users for parameters, validate them against the generated schema, and receive structured JSON responses—all without custom code. This plug‑and‑play model empowers developers to expose rich, typed APIs to conversational agents quickly and reliably.