XiYan MCP Server

A Model Context Protocol (MCP) server that enables natural language queries to databases
_{powered by XiYan-SQL, SOTA of text-to-sql on open benchmarks}

## Table of Contents - [Features](#features) - [Preview](#preview) - [Architecture](#architecture) - [Best Practice](#best-practice) - [Tools Preview](#tools-preview) - [Installation](#installation) - [Installing from pip](#installing-from-pip) - [Installing from Smithery.ai](#installing-from-smitheryai) - [Configuration](#configuration) - [LLM Configuration](#llm-configuration) - [General LLMs](#general-llms) - [Text-to-SQL SOTA model](#text-to-sql-sota-model) - [Local Model](#local-model) - [Database Configuration](#database-configuration) - [MySQL](#mysql) - [PostgreSQL](#postgresql) - [Launch](#launch) - [Claude Desktop](#claude-desktop) - [Cline](#cline) - [Goose](#goose) - [Cursor](#cursor) - [It Does Not Work](#it-does-not-work) - [Citation](#citation) ## Features - 🌐 Fetch data by natural language through [XiYanSQL](https://github.com/XGenerationLab/XiYan-SQL) - 🤖 Support general LLMs (GPT,qwenmax), Text-to-SQL SOTA model - 💻 Support pure local mode (high security!) - 📝 Support MySQL and PostgreSQL. - 🖱️ List available tables as resources - 🔧 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](#Configuration)). Another mode is local mode, which is more secure. It does not require the API key. ![architecture.png](imgs/architecture.png) ### Best practice and reports ["Build a local data assistant using MCP + Modelscope API-Inference without writing a single line of code"](https://mp.weixin.qq.com/s/tzDelu0W4w6t9C0_yYRbHA) ["Xiyan MCP on Modelscope"](https://modelscope.cn/headlines/article/1142) ### 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](https://github.com/modelscope/MCPBench) and the report ["Evaluation Report on MCP Servers"](https://arxiv.org/abs/2504.11094). ![exp_mcpbench.png](imgs/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: ```bash pip install xiyan-mcp-server ``` After that you can directly run the server by: ```bash python -m xiyan_mcp_server ``` But it does not provide any functions until you complete following config. You will get a yml file. After that you can run the server by: ```yaml env YML=path/to/yml python -m xiyan_mcp_server ``` ### Installing from Smithery.ai See [@XGenerationLab/xiyan_mcp_server](https://smithery.ai/server/@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: ```yaml model: name: "XGenerationLab/XiYanSQL-QwenCoder-32B-2412" key: "" url: "https://api-inference.modelscope.cn/v1/" database: host: "localhost" port: 3306 user: "root" password: "" database: "" ``` ### 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: ```yaml 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: ```yaml 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](https://bird-bench.github.io/). There are two ways to use the model. You can use either of them. (1) [Modelscope](https://www.modelscope.cn/models/XGenerationLab/XiYanSQL-QwenCoder-32B-2412), (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: ```yaml model: name: "XGenerationLab/XiYanSQL-QwenCoder-32B-2412" key: "" url: "https://api-inference.modelscope.cn/v1/" ``` Read our [model description](https://www.modelscope.cn/models/XGenerationLab/XiYanSQL-QwenCoder-32B-2412) 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: ```yaml 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. ```yaml model: name: "xiyansql-qwencoder-32b" key: "KEY" url: "https://xiyan-stream.biz.aliyun.com/service/api/xiyan-sql" database: ``` Note: this model service is just for trial, if you need to use it in production, please contact us. Alternatively, you can also deploy the model [XiYanSQL-qwencoder-32B](https://github.com/XGenerationLab/XiYanSQL-QwenCoder) on your own server. #### Local Model Note: the local model is slow (about 12 seconds per query on my macbook). If you need a stable and fast service, we still recommend to use the modelscope version. To run xiyan_mcp_server in local mode, you need 1) a PC/Mac with at least 16GB RAM 2) 6GB disk space Step 1: Install additional Python packages ```bash pip install flask modelscope torch==2.2.2 accelerate>=0.26.0 numpy=2.2.3 ``` Step 2: (optional) manually download the model We recommend [xiyansql-qwencoder-3b](https://www.modelscope.cn/models/XGenerationLab/XiYanSQL-QwenCoder-3B-2502/). You can manually download the model by ```bash modelscope download --model XGenerationLab/XiYanSQL-QwenCoder-3B-2502 ``` It will take you 6GB disk space. Step 3: download the script and run server. src/xiyan_mcp_server/local_xiyan_server.py ```bash python local_xiyan_server.py ``` The server will be running on http://localhost:5090/ Step 4: prepare config and run xiyan_mcp_server the config.yml should be like: ```yml model: name: "xiyansql-qwencoder-3b" key: "KEY" url: "http://127.0.0.1:5090" ``` Till now the local mode is ready. ### 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 ```yaml database: host: "localhost" port: 3306 user: "root" password: "" database: "" ``` #### PostgreSQL Step 1: Install Python packages ```bash pip install psycopg2 ``` Step 2: prepare the config.yml like this: ```yaml database: dialect: "postgresql" host: "localhost" port: 5432 user: "" password: "" database: "" ``` Note that ``dialect`` should be ``postgresql`` for postgresql. ## Launch ### Claude Desktop Add this in your Claude Desktop config file, ref Claude Desktop config example ```json { "mcpServers": { "xiyan-mcp-server": { "command": "python", "args": [ "-m", "xiyan_mcp_server" ], "env": { "YML": "PATH/TO/YML" } } } } ``` ### Cline Prepare the config like [Claude Desktop](#claude-desktop) ### Goose Add following command in the config, ref Goose config example ```yaml env YML=path/to/yml python -m xiyan_mcp_server ``` ### Cursor Use the same command like [Goose](#goose). ### Witsy Add following in command: ```yaml python -m xiyan_mcp_server ``` Add an env: key is YML and value is the path to your yml file. Ref Witsy config example ## It Does Not Work! Contact us: Ding Group钉钉群｜ Follow me on Weibo ## Citation If you find our work helpful, feel free to give us a cite. ```bib @article{xiyansql, title={A Preview of XiYan-SQL: A Multi-Generator Ensemble Framework for Text-to-SQL}, author={Yingqi Gao and Yifu Liu and Xiaoxia Li and Xiaorong Shi and Yin Zhu and Yiming Wang and Shiqi Li and Wei Li and Yuntao Hong and Zhiling Luo and Jinyang Gao and Liyu Mou and Yu Li}, year={2024}, journal={arXiv preprint arXiv:2411.08599}, url={https://arxiv.org/abs/2411.08599}, primaryClass={cs.AI} } ```

natural language query

XiYan MCP Server

XiYan MCP Server