PawSQL MCP Server
A SQL optimization service providing performance analysis and optimization suggestions through an API.
PawSQL MCP Server
Project Overview
PawSQL MCP Server is a SQL optimization service developed based on Spring AI, providing SQL performance analysis and optimization suggestions. It runs as an MCP (Model Control Protocol) server and provides SQL optimization capabilities through API interfaces.
Key Features
- Supports both workspace and workspace-free optimization modes
- Provides SQL rewriting and index optimization suggestions
- Visual execution plan analysis (for database-connected workspaces)
- Performance evaluation reports
Supported Databases
- MySQL
- PostgreSQL
- Oracle
- KingbaseES
- openGauss
- MogDB
- GaussDB
- DWS
Installation Guide
-
Configure Claude Desktop:
- Open Claude Desktop
- Select "Settings", click "Developer" tab
- Click "Edit Config"
- Add MCP server configuration
- Save the file
- Restart Claude Desktop
-
MCP Server Configuration Template:
{
"mcpServers": {
"pawsql": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e", "PAWSQL_EDITION=<edition>",
"-e", "PAWSQL_API_BASE_URL=<api-url>",
"-e", "PAWSQL_API_EMAIL=<email>",
"-e", "PAWSQL_API_PASSWORD=<password>",
"pawsql/pawsql-mcp-server:latest"
]
}
}
}
- Configuration Parameters:
<edition>
: Choose one of the following editionsenterprise
- Enterprise Editioncloud
- Cloud Editioncommunity
- Community Edition
<api-url>
: API service address<email>
: Account email<password>
: Account password
- Edition Configuration Examples:
Enterprise Edition:
{
"mcpServers": {
"pawsql": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"-e", "PAWSQL_EDITION=enterprise",
"-e", "PAWSQL_API_BASE_URL=https://your-enterprise-api.com",
"-e", "PAWSQL_API_EMAIL=admin@company.com",
"-e", "PAWSQL_API_PASSWORD=your-password",
"pawsql/pawsql-mcp-server:latest"
]
}
}
}
Cloud Edition:
{
"mcpServers": {
"pawsql": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"-e", "PAWSQL_EDITION=cloud",
"-e", "PAWSQL_API_EMAIL=user@example.com",
"-e", "PAWSQL_API_PASSWORD=your-password",
"pawsql/pawsql-mcp-server:latest"
]
}
}
}
Community Edition:
{
"mcpServers": {
"pawsql": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"-e", "PAWSQL_EDITION=community",
"-e", "PAWSQL_API_BASE_URL=https://community-api.pawsql.com",
"pawsql/pawsql-mcp-server:latest"
]
}
}
}
Using in Claude
After configuration, you can use PawSQL MCP Server in different ways. Here are some examples:
1. Getting Workspace Information
Before using workspace-based optimization, you need to get the workspace information:
User: What workspaces are available?
Assistant: Here are the available workspaces:
| Workspace Name | Workspace ID | Database Type | Can Validate Optimization | Status |
|---------------|--------------|--------------|------------------------|--------|
| WS_MySQL_202505241801 | 1926217077522944002 | mysql | Yes | success |
2. SQL Optimization Methods
Method 1: Simple Query Optimization
Provide database type and SQL query:
Help me optimize this mysql query:
select *
from customer
where c_custkey = (select max(o_custkey)
from orders
where subdate(o_orderdate, interval '1' DAY) < '2022-12-20')
Method 2: Optimization with Table Structure
Provide database type, table structure (DDL), and SQL query:
I want to optimize this mysql query, here's the table structure:
CREATE TABLE `customer` (
`C_CUSTKEY` int NOT NULL,
`C_NAME` varchar(25) NOT NULL,
`C_ADDRESS` varchar(40) NOT NULL,
`C_NATIONKEY` int NOT NULL,
`C_PHONE` char(15) NOT NULL,
`C_ACCTBAL` decimal(15,2) NOT NULL,
`C_MKTSEGMENT` char(10) NOT NULL,
`C_COMMENT` varchar(117) NOT NULL,
PRIMARY KEY `PK_IDX1614428511` (`C_CUSTKEY`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_bin;
CREATE TABLE `orders` (
`O_ORDERKEY` int NOT NULL,
`O_CUSTKEY` int NOT NULL,
`O_ORDERSTATUS` char(1) NOT NULL,
`O_TOTALPRICE` decimal(15,2) NOT NULL,
`O_ORDERDATE` date NOT NULL,
`O_ORDERPRIORITY` char(15) NOT NULL,
`O_CLERK` char(15) NOT NULL,
`O_SHIPPRIORITY` int NOT NULL,
`O_COMMENT` varchar(79) NOT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci;
select *
from customer
where c_custkey = (select max(o_custkey)
from orders
where subdate(o_orderdate, interval '1' DAY) < '2022-12-20')
Method 3: Workspace-based Optimization
Provide workspace name/ID and SQL query for more accurate optimization with actual database context:
Optimize this query in workspace WS_MySQL_202505241801:
select *
from customer
where c_custkey = (select max(o_custkey)
from orders
where subdate(o_orderdate, interval '1' DAY) < '2022-12-20')
Note on Workspace Information
You can obtain workspace information through two methods:
- Using PawSQL MCP Tools: Ask the AI assistant to list available workspaces using built-in commands
- Web Interface: Visit your configured PawSQL service web interface to view and manage workspaces
Optimization Report Description
The system will return an optimization report containing the following:
-
Analysis Report Link
- View detailed analysis results
-
Analysis Environment Details
- Contains SQL analysis context information
-
Optimization Suggestions
- SQL rewriting suggestions
- Index optimization suggestions
- Execution plan analysis (for validation-enabled workspaces only)
- Performance improvement estimates
Related Servers
GreptimeDB
Provides AI assistants with a secure and structured way to explore and analyze data in GreptimeDB.
MySQL MCP Server
Provides access to a MySQL database, allowing agents to execute SQL queries.
SAS XPT MCP Server by CData
A Model Context Protocol (MCP) server for SAS XPT files, powered by the CData JDBC Driver.
Notion Content Database
Manage content databases in Notion using the Notion API.
Elasticsearch Security Solution
An Elasticsearch server focused on security and threat analysis. Requires a valid Elasticsearch license (trial, platinum, or enterprise) for connection.
RBDC MCP Server
An MCP-based database server with support for SQLite, MySQL, PostgreSQL, and MSSQL.
BigQuery
Explore, query, and manage data in Google BigQuery.
PostgreSQL MCP Server by CData
A read-only MCP server for PostgreSQL, enabling LLMs to query live data from PostgreSQL databases.
Pinecone
Read and write to a Pinecone vector database using the Model Context Protocol.
DBeaver MCP Server
Integrates with DBeaver to provide AI assistants access to over 200 database types using existing connections.