XiYan MCP Server

by XGenerationLab

239 stars
478 downloads
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About

A Model Context Protocol (MCP) server that enables natural language queries to databases

Details

Author
XGenerationLab
GitHub stars
239
Downloads
478
Categories
Database, Other, AI

- Query databases using natural language via XiYanSQL
- Supports general LLMs (GPT, Qwen-max) and a SOTA text-to-SQL model
- Runs in pure local mode for high security
- Works with MySQL and PostgreSQL databases
- Lists available tables and reads table contents as resources

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name XiYan MCP Server
    Command (node, npx, python, etc.)

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

Install the server with pip install xiyan-mcp-server, then provide a YAML configuration file specifying the LLM model, API key, database credentials, and transport protocol (stdio or sse). Launch the server with YML=path/to/yml python -m xiyan_mcp_server and connect it to a supported MCP client.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "xiyan mcp server": {
            "xiyan-mcp-server": {
                "command": "python",
                "args": [
                    "-m",
                    "xiyan_mcp_server"
                ],
                "env": {
                    "YML": "PATH/TO/YML"
                }
            }
        }
    }
}

McpServers

{
    "xiyan-mcp-server": {
        "command": "python",
        "args": [
            "-m",
            "xiyan_mcp_server"
        ],
        "env": {
            "YML": "PATH/TO/YML"
        }
    }
}

<h1 align="center">XiYan MCP Server</h1>
<p align="center">
<a href="https://github.com/XGenerationLab/XiYan-SQL">MCP Playwright</a>
</p>
<p align="center">
<b>A Model Context Protocol (MCP) server that enables natural language queries to databases</b><br/>
<sub>powered by <a href="https://github.com/XGenerationLab/XiYan-SQL" >XiYan-SQL</a>, SOTA of text-to-sql on open benchmarks</sub>
</p>
<p align="center">
πŸ’» <a href="https://github.com/XGenerationLab/xiyan_mcp_server" >XiYan-mcp-server</a> |
🌐 <a href="https://github.com/XGenerationLab/XiYan-SQL" >XiYan-SQL</a> |
πŸ“– <a href="https://arxiv.org/abs/2507.04701"> Arxiv</a> |
πŸ† <a href="https://github.com/XGenerationLab/XiYanSQL-QwenCoder" >XiYanSQL Model</a> |
πŸ“„ <a href="https://paperswithcode.com/paper/xiyan-sql-a-multi-generator-ensemble" >PapersWithCode</a>
πŸ€— <a href="https://huggingface.co/collections/XGenerationLab/xiyansql-models-67c9844307b49f87436808fc">HuggingFace</a> |
πŸ€– <a href="https://modelscope.cn/collections/XiYanSQL-Models-4483337b614241" >ModelScope</a> |
πŸŒ• <a href="https://bailian.console.aliyun.com/xiyan">ζžθ¨€GBI</a>
<br />
MCP Server
<a href="https://arxiv.org/abs/2411.08599"></a>
<a href="https://opensource.org/licenses/Apache-2.0">
License: Apache 2.0
</a>
<a href="https://pepy.tech/projects/xiyan-mcp-server">PyPI Downloads</a>

Trust Score
<a href="https://smithery.ai/server/@XGenerationLab/xiyan_mcp_server">Smithery Installs</a>
<a href="https://github.com/XGenerationLab/xiyan_mcp_server" target="_blank">
GitHub stars
</a>
<br />
<a href="https://github.com/XGenerationLab/xiyan_mcp_server" >English</a> | <a href="https://github.com/XGenerationLab/xiyan_mcp_server/blob/main/README_zh.md"> δΈ­ζ–‡ </a> | <a href="https://github.com/XGenerationLab/xiyan_mcp_server/blob/main/README_ja.md"> ζ—₯本θͺž </a><br />
<a href="https://github.com/XGenerationLab/xiyan_mcp_server/blob/main/imgs/dinggroup_out.png">Ding Groupι’‰ι’‰ηΎ€</a>|
<a href="https://weibo.com/u/2540915670" target="_blank">Follow me on Weibo</a>
</p>

Table of Contents

- Features
- Preview
- Architecture
- Best Practice
- Tools Preview
- Installation
- Installing from pip
- Installing from Smithery.ai
- Configuration
- LLM Configuration
- General LLMs
- Text-to-SQL SOTA model
- Local Model
- Database Configuration
- MySQL
- PostgreSQL
- Launch
- Claude Desktop
- Cline
- Goose
- Cursor
- It Does Not Work
- Citation

Features

- 🌐 Fetch data by natural language through XiYanSQL - πŸ€– Support general LLMs (GPT,qwenmax), Text-to-SQL SOTA model - πŸ’» Support pure local mode (high security!) - πŸ“ Support MySQL and PostgreSQL. - πŸ–±οΈ List available tables as resources - πŸ”§ Read table contents

Preview

Architecture

There are two ways to integrate this server in your project, as shown below: The left is remote mode, which is the default mode. It requires an API key to access the xiyanSQL-qwencoder-32B model from service provider (see Configuration). Another mode is local mode, which is more secure. It does not require the API key.

architecture.png

Best practice and reports

"Build a local data assistant using MCP + Modelscope API-Inference without writing a single line of code"

"Xiyan MCP on Modelscope"

Evaluation on MCPBench

The following figure illustrates the performance of the XiYan MCP server as measured by the MCPBench benchmark. The XiYan MCP server demonstrates superior performance compared to both the MySQL MCP server and the PostgreSQL MCP server, achieving a lead of 2-22 percentage points. The detailed experiment results can be found at MCPBench and the report "Evaluation Report on MCP Servers".

exp_mcpbench.png

Tools Preview

- The tool `get_data provides a natural language interface for retrieving data from a database. This server will convert the input natural language into SQL using a built-in model and call the database to return the query results.

- The {dialect}://{table_name} resource allows obtaining a portion of sample data from the database for model reference when a specific table_name is specified.
- The
{dialect}:// resource will list the names of the current databases

Installation

Installing from pip

Python 3.11+ is required.
You can install the server through pip, and it will install the latest version:

pip install xiyan-mcp-server

If you want to install the development version from source, you can install from source code on github:

pip install git+https://github.com/XGenerationLab/xiyan_mcp_server.git

Installing from Smithery.ai

See @XGenerationLab/xiyan_mcp_server

Not fully tested.

Configuration

You need a YAML config file to configure the server.
A default config file is provided in config_demo.yml which looks like this:

mcp:
  transport: "stdio"
model:
  name: "XGenerationLab/XiYanSQL-QwenCoder-32B-2412"
  key: ""
  url: "https://api-inference.modelscope.cn/v1/"
database:
  host: "localhost"
  port: 3306
  user: "root"
  password: ""
  database: ""

MCP Configuration

You can set the transport protocol to
stdio or sse.

STDIO

For stdio protocol, you can set just like this:
mcp:
  transport: "stdio"

SSE

For sse protocol, you can set mcp config as below:
mcp:
  transport: "sse"
  port: 8000
  log_level: "INFO"
The default port is
8000. You can change the port if needed. The default log level is ERROR. We recommend to set log level to INFO for more detailed information.

Other configurations like debug, host, sse_path, message_path can be customized as well, but normally you don't need to modify them.

LLM Configuration

Name is the name of the model to use, key is the API key of the model, url is the API url of the model. We support following models.

| versions | general LLMs(GPT,qwenmax) | SOTA model by Modelscope | SOTA model by Dashscope | Local LLMs |
|----------|-------------------------------|--------------------------------------------|-----------------------------------------------------------|-----------------------|
| description| basic, easy to use | best performance, stable, recommand | best performance, for trial | slow, high-security |
| name | the official model name (e.g. gpt-3.5-turbo,qwen-max) | XGenerationLab/XiYanSQL-QwenCoder-32B-2412 | xiyansql-qwencoder-32b | xiyansql-qwencoder-3b |
| key | the API key of the service provider (e.g. OpenAI, Alibaba Cloud) | the API key of modelscope | the API key via email | "" |
| url | the endpoint of the service provider (e.g."https://api.openai.com/v1") | https://api-inference.modelscope.cn/v1/ | https://xiyan-stream.biz.aliyun.com/service/api/xiyan-sql | http://localhost:5090 |

General LLMs

If you want to use the general LLMs, e.g. gpt3.5, you can directly config like this:
model:
  name: "gpt-3.5-turbo"
  key: "YOUR KEY "
  url: "https://api.openai.com/v1"
database:

If you want to use Qwen from Alibaba, e.g. Qwen-max, you can use following config:

model:
name: "qwen-max"
key: "YOUR KEY "
url: "https://dashscope.aliyuncs.com/compatible-mode/v1"
database:

Text-to-SQL SOTA model


We recommend the XiYanSQL-qwencoder-32B (https://github.com/XGenerationLab/XiYanSQL-QwenCoder), which is the SOTA model in text-to-sql, see Bird benchmark.
There are two ways to use the model. You can use either of them.
(1) Modelscope, (2) Alibaba Cloud DashScope.

(1) Modelscope version
You need to apply a
key of API-inference from Modelscope, https://www.modelscope.cn/docs/model-service/API-Inference/intro Then you can use the following config:
model:
  name: "XGenerationLab/XiYanSQL-QwenCoder-32B-2412"
  key: ""
  url: "https://api-inference.modelscope.cn/v1/"

Read our model description for more details.

(2) Dashscope version

We deployed the model on Alibaba Cloud DashScope, so you need to set the following environment variables:
Send me your email to get the
key. ( godot.lzl@alibaba-inc.com )
In the email, please attach the following information:

name: "YOUR NAME",
email: "YOUR EMAIL",
organization: "your college or Company or Organization"

We will send you a
key according to your email. And you can fill the key in the yml file.
The
key will be expired by 1 month or 200 queries or other legal restrictions.

model:
  name: "xiyansql-qwencoder-32b"
  key: "KEY"
  url: "https://xiyan-stream.biz.aliyun.com/service/api/xiyan-sql"

Note: this model service is just for trial, if you need to use it in production, please contact us.

(3) Local version
Alternatively, you can also deploy the model XiYanSQL-qwencoder-32B on your own server. See Local Model for more details.

Database Configuration

host, port, user, password, database are the connection information of the database.

You can use local or any remote databases. Now we support MySQL and PostgreSQL(more dialects soon).

MySQL

database:
  host: "localhost"
  port: 3306
  user: "root"
  password: ""
  database: ""

PostgreSQL

Step 1: Install Python packages
pip install psycopg2
Step 2: prepare the config.yml like this:
database:
  dialect: "postgresql"
  host: "localhost"
  port: 5432
  user: ""
  password: ""
  database: ""

Note that dialect should be postgresql for postgresql.

Launch

Server Launch

If you want to launch server with sse, you have to run the following command in a terminal:

YML=path/to/yml python -m xiyan_mcp_server

Then you should see the information on http://localhost:8000/sse in your browser. (Defaultly, change if your mcp server runs on other host/port)

Otherwise, if you use stdio transport protocol, you usually declare the mcp server command in specific mcp application instead of launching it in a terminal.
However, you can still debug with this command if needed.

Client Setting

Claude Desktop

Add this in your Claude Desktop config file, ref <a href="https://github.com/XGenerationLab/xiyan_mcp_server/blob/main/imgs/claude_desktop.jpg">Claude Desktop config example</a>
{
    "mcpServers": {
        "xiyan-mcp-server": {
            "command": "/xxx/python",
            "args": [
                "-m",
                "xiyan_mcp_server"
            ],
            "env": {
                "YML": "PATH/TO/YML"
            }
        }
    }
}
Please note that the Python command here requires the complete path to the Python executable (
/xxx/python); otherwise, the Python interpreter cannot be found. You can determine this path by using the command which python. The same applies to other applications as well.

Claude Desktop currently does not support the SSE transport protocol.

Cline

Prepare the config like Claude Desktop

Goose

If you use
stdio, add following command in the config, ref <a href="https://github.com/XGenerationLab/xiyan_mcp_server/blob/main/imgs/goose.jpg">Goose config example</a>
env YML=path/to/yml /xxx/python -m xiyan_mcp_server
Otherwise, if you use
sse, change Type to SSE and set the endpoint to http://127.0.0.1:8000/sse

Cursor

Use the similar command as follows.

For stdio:

{
"mcpServers": {
"xiyan-mcp-server": {
"command": "/xxx/python",
"args": [
"-m",
"xiyan_mcp_server"
],
"env": {
"YML": "path/to/yml"
}
}
}
}

For
sse`:
{
"mcpServers": {
"xiyan_mcp_server_1": {
"url": "http://localhost:8000/sse"
}
}
}

Witsy

Add following in command:
/xxx/python -m xiyan_mcp_server
Add an env: key is YML and value is the path to your yml file. Ref <a href="https://github.com/XGenerationLab/xiyan_mcp_server/blob/main/imgs/witsy.jpg">Witsy config example</a>

Contact us:

If you are interested in our research or products, please feel free to contact us.

Contact Information:

Yifu Liu, zhencang.lyf@alibaba-inc.com

Join Our DingTalk Group

<a href="https://github.com/XGenerationLab/XiYan-SQL/blob/main/xiyansql_dingding.png">Ding Groupι’‰ι’‰ηΎ€</a>

Other Related Links

MseeP.ai Security Assessment Badge

Citation

If you find our work helpful, feel free to give us a cite.
@article{XiYanSQL,
      title={XiYan-SQL: A Novel Multi-Generator Framework For Text-to-SQL}, 
      author={Yifu Liu and Yin Zhu and Yingqi Gao and Zhiling Luo and Xiaoxia Li and Xiaorong Shi and Yuntao Hong and Jinyang Gao and Yu Li and Bolin Ding and Jingren Zhou},
      year={2025},
      eprint={2507.04701},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2507.04701}, 
}
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