XiYan MCP Server

XiYan MCP Server is a specialized Model Context Protocol (MCP) implementation that turns natural‑language questions into SQL queries against relational databases. By exposing a lightweight HTTP interface, it lets AI assistants such as Claude or other LLM‑powered agents fetch structured data without writing code. The server harnesses the XiYanSQL engine—an ensemble of state‑of‑the‑art text‑to‑SQL models—to translate user intent into accurate SQL statements, then executes those queries on MySQL or PostgreSQL backends and returns the results as JSON. This capability removes the need for developers to build custom database connectors or craft SQL manually, enabling a frictionless data‑driven conversation layer.

The core value proposition is twofold. First, it bridges the gap between conversational AI and relational data stores, allowing agents to answer factual queries (“How many orders did customer X place last month?”) or perform ad‑hoc analytics on the fly. Second, it abstracts away database credentials and schema details; developers only need to expose a list of tables as resources, and the MCP automatically makes them discoverable for the LLM. The server’s “list tables” and “read table contents” tools give assistants a sandboxed view of the schema, ensuring that queries stay within authorized boundaries.

Key capabilities include:

• Natural‑language data retrieval via XiYanSQL, supporting complex joins and aggregations.
• Multi‑model flexibility: plug in any LLM (GPT, QwenMax) for general dialogue or switch to the dedicated text‑to‑SQL model for higher accuracy.
• Pure local deployment: run entirely on a private machine, eliminating data egress and satisfying strict security policies.
• Database agnostic: native support for MySQL and PostgreSQL with minimal configuration.
• Resource discovery: the server automatically lists available tables, allowing LLMs to introspect the schema before querying.

In practice, XiYan MCP is ideal for building knowledge‑base assistants in enterprises where internal data resides in legacy databases. Use cases include customer support bots that pull order histories, BI tools that let analysts ask questions in plain English, or chat‑based interfaces for financial dashboards. By integrating the server with an MCP‑compatible client (Claude Desktop, Goose, or Cursor), developers can embed robust data access into conversational workflows with just a few configuration steps.

What sets XiYan apart is its combination of model‑level and database‑level integration. The server not only exposes the database as a resource but also couples it with a top‑tier text‑to‑SQL engine, delivering higher query accuracy than generic LLMs. Coupled with its local‑only mode and straightforward resource listing, it offers a secure, developer‑friendly path to turning any relational database into an AI‑powered knowledge graph.