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SQL Connector MCP

An MCP (Model Context Protocol) server that provides SQL database connectivity for AI assistants like Claude.

Features

  • Database Exploration: List all table names or filter tables by substring
  • Schema Inspection: Get detailed schema definitions including columns, types, primary keys, and foreign key relationships
  • Query Execution: Execute SQL queries with parameterized inputs and formatted results
  • Form Fetching: Retrieve form schemas from database based on trigger keywords

Installation

pip install sql-connector-mcp

Configuration

Set the following environment variables:

# Required: Database connection URL
DB_URL=mysql://user:password@host:port/database

# Optional: Maximum characters for query results (default: 4000)
EXECUTE_QUERY_MAX_CHARS=4000

# Optional: Path for saving full result sets
CLAUDE_LOCAL_FILES_PATH=/path/to/files

Usage

Run the MCP server:

python -m sql_connector_mcp.server

Opens the caldue code or cursor or any ai ide and add this json "my_database": { "command": "python", "args": ["-m", "sql_connector_mcp.server"], "env": { "DB_URL": "your dbatabase url" }

Available Tools

Tool Description
all_table_names() Returns all table names in the database
filter_table_names(q) Returns table names containing the substring q
schema_definitions(table_names) Returns schema and relationship info for specified tables
execute_query(query, params) Executes a SQL query and returns formatted results
fetch_form(query_text, db_name) Fetches form schema based on trigger keywords

Requirements

  • Python >= 3.7
  • SQLAlchemy
  • PyMySQL
  • FastMCP

License

MIT License

Author

Battula Anil Kumar (anilkumarbaatula@gmail.com)

Metadata

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