IOG MCP Server

The IOG Model Context Protocol (MCP) Server is a lightweight, standalone implementation designed to bridge AI assistants with external data and functionality. By exposing a standardized set of MCP endpoints, it allows tools such as calculators, web search, and domain‑specific data retrieval to be discovered and invoked by AI clients like Claude or other MCP‑compatible assistants. This eliminates the need for custom integrations and gives developers a single, consistent interface to add new capabilities.

At its core, the server hosts a tool registry that includes ready‑made utilities for performing arithmetic calculations and querying web search results. Beyond these generic tools, it also offers data retrieval functions that tap into locally stored JSON files containing persona and product information. Each tool is described with a comprehensive JSON schema, ensuring that clients can validate parameters before execution and receive predictable responses. The standard MCP endpoints ( for discovery and for invocation) make it trivial to list available tools or run a specific one with the required arguments.

Developers benefit from this architecture in several ways. First, the server can be embedded into existing applications—such as Windsurf—without requiring a full AI stack. The provided integration example demonstrates how to register the MCP server with Windsurf, enabling downstream services to call tools through a familiar API. Second, because the tool definitions are JSON‑schema driven, adding new capabilities is as simple as extending a JavaScript object; the server automatically updates the discovery endpoint. This modularity encourages rapid prototyping and experimentation.

Typical use cases include building conversational agents that need to answer product‑related queries, fetch persona details for role‑playing scenarios, or perform quick calculations on the fly. In an e‑commerce setting, a customer support chatbot could retrieve product specifications from the file while simultaneously calculating discount totals. In a research environment, an AI assistant could pull persona attributes to tailor responses or execute web searches for up‑to‑date information. Because the MCP server exposes a clean REST interface, these scenarios can be integrated into existing CI/CD pipelines or microservice architectures with minimal friction.

What sets the IOG MCP Server apart is its focus on simplicity and extensibility. It ships with a fully functional example for Windsurf, demonstrates clear JSON schema usage, and follows the MCP standard rigorously. Developers who are already familiar with MCP concepts will find that this server reduces boilerplate, accelerates tool integration, and provides a reliable foundation for building sophisticated AI‑powered workflows.