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mcp-sqlalchemy-server

MCP.Pizza Chef: OpenLinkSoftware

mcp-sqlalchemy-server is a lightweight MCP server that provides ODBC database access via FastAPI, pyodbc, and SQLAlchemy. It supports fetching schemas, tables, and detailed table descriptions, including columns, keys, and data types. Compatible with Virtuoso DBMS and other SQLAlchemy-supported databases, it enables executing stored procedures and queries with JSONL or markdown output formats.

Use This MCP server To

Fetch and list all database schemas dynamically Retrieve detailed table metadata including keys and data types Search and filter tables by name substrings Execute stored procedures on Virtuoso DBMS Run SQL queries and return results in JSONL or markdown Integrate database context into LLM workflows via MCP Enable real-time database inspection and querying through MCP

README


MCP Server ODBC via SQLAlchemy

A lightweight MCP (Model Context Protocol) server for ODBC built with FastAPI, pyodbc, and SQLAlchemy. This server is compatible with Virtuoso DBMS and other DBMS backends that implement a SQLAlchemy provider.

mcp-client-and-servers|648x499


Features

  • Get Schemas: Fetch and list all schema names from the connected database.
  • Get Tables: Retrieve table information for specific schemas or all schemas.
  • Describe Table: Generate a detailed description of table structures, including:
    • Column names and data types
    • Nullable attributes
    • Primary and foreign keys
  • Search Tables: Filter and retrieve tables based on name substrings.
  • Execute Stored Procedures: In the case of Virtuoso, execute stored procedures and retrieve results.
  • Execute Queries:
    • JSONL result format: Optimized for structured responses.
    • Markdown table format: Ideal for reporting and visualization.

Prerequisites

  1. Install uv:

    pip install uv

    Or use Homebrew:

    brew install uv
  2. unixODBC Runtime Environment Checks:

  3. Check installation configuration (i.e., location of key INI files) by running: odbcinst -j

  4. List available data source names by running: odbcinst -q -s

  5. ODBC DSN Setup: Configure your ODBC Data Source Name (~/.odbc.ini) for the target database. Example for Virtuoso DBMS:

    [VOS]
    Description = OpenLink Virtuoso
    Driver = /path/to/virtodbcu_r.so
    Database = Demo
    Address = localhost:1111
    WideAsUTF16 = Yes
    
  6. SQLAlchemy URL Binding: Use the format:

    virtuoso+pyodbc://user:password@VOS
    

Installation

Clone this repository:

git clone https://github.com/OpenLinkSoftware/mcp-sqlalchemy-server.git
cd mcp-sqlalchemy-server

Environment Variables

Update your .envby overriding the defaults to match your preferences

ODBC_DSN=VOS
ODBC_USER=dba
ODBC_PASSWORD=dba
API_KEY=xxx

Configuration

For Claude Desktop users: Add the following to claude_desktop_config.json:

{
  "mcpServers": {
    "my_database": {
      "command": "uv",
      "args": ["--directory", "/path/to/mcp-sqlalchemy-server", "run", "mcp-sqlalchemy-server"],
      "env": {
        "ODBC_DSN": "dsn_name",
        "ODBC_USER": "username",
        "ODBC_PASSWORD": "password",
        "API_KEY": "sk-xxx"
      }
    }
  }
}

Usage

Database Management System (DBMS) Connection URLs

Here are the pyodbc URL examples for connecting to DBMS systems that have been tested using this mcp-server.

Database URL Format
Virtuoso DBMS virtuoso+pyodbc://user:password@ODBC_DSN
PostgreSQL postgresql://user:password@localhost/dbname
MySQL mysql+pymysql://user:password@localhost/dbname
SQLite sqlite:///path/to/database.db
Once connected, you can interact with your WhatsApp contacts through Claude, leveraging Claude's AI capabilities in your WhatsApp conversations.

Tools Provided

Overview

name description
podbc_get_schemas List database schemas accessible to connected database management system (DBMS).
podbc_get_tables List tables associated with a selected database schema.
podbc_describe_table Provide the description of a table associated with a designated database schema. This includes information about column names, data types, nulls handling, autoincrement, primary key, and foreign keys
podbc_filter_table_names List tables, based on a substring pattern from the q input field, associated with a selected database schema.
podbc_query_database Execute a SQL query and return results in JSONL format.
podbc_execute_query Execute a SQL query and return results in JSONL format.
podbc_execute_query_md Execute a SQL query and return results in Markdown table format.
podbc_spasql_query Execute a SPASQL query and return results.
podbc_sparql_query Execute a SPARQL query and return results.
podbc_virtuoso_support_ai Interact with the Virtuoso Support Assistant/Agent -- a Virtuoso-specific feature for interacting with LLMs

Detailed Description

  • podbc_get_schemas

    • Retrieve and return a list of all schema names from the connected database.
    • Input parameters:
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • dsn (string, optional): ODBC data source name. Defaults to "Local Virtuoso".
    • Returns a JSON string array of schema names.
  • podbc_get_tables

    • Retrieve and return a list containing information about tables in a specified schema. If no schema is provided, uses the connection's default schema.
    • Input parameters:
      • schema (string, optional): Database schema to filter tables. Defaults to connection default.
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • dsn (string, optional): ODBC data source name. Defaults to "Local Virtuoso".
    • Returns a JSON string containing table information (e.g., TABLE_CAT, TABLE_SCHEM, TABLE_NAME, TABLE_TYPE).
  • podbc_filter_table_names

    • Filters and returns information about tables whose names contain a specific substring.
    • Input parameters:
      • q (string, required): The substring to search for within table names.
      • schema (string, optional): Database schema to filter tables. Defaults to connection default.
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • dsn (string, optional): ODBC data source name. Defaults to "Local Virtuoso".
    • Returns a JSON string containing information for matching tables.
  • podbc_describe_table

    • Retrieve and return detailed information about the columns of a specific table.
    • Input parameters:
      • schema (string, required): The database schema name containing the table.
      • table (string, required): The name of the table to describe.
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • dsn (string, optional): ODBC data source name. Defaults to "Local Virtuoso".
    • Returns a JSON string describing the table's columns (e.g., COLUMN_NAME, TYPE_NAME, COLUMN_SIZE, IS_NULLABLE).
  • podbc_query_database

    • Execute a standard SQL query and return the results in JSON format.
    • Input parameters:
      • query (string, required): The SQL query string to execute.
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • dsn (string, optional): ODBC data source name. Defaults to "Local Virtuoso".
    • Returns query results as a JSON string.
  • podbc_query_database_md

    • Execute a standard SQL query and return the results formatted as a Markdown table.
    • Input parameters:
      • query (string, required): The SQL query string to execute.
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • dsn (string, optional): ODBC data source name. Defaults to "Local Virtuoso".
    • Returns query results as a Markdown table string.
  • podbc_query_database_jsonl

    • Execute a standard SQL query and return the results in JSON Lines (JSONL) format (one JSON object per line).
    • Input parameters:
      • query (string, required): The SQL query string to execute.
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • dsn (string, optional): ODBC data source name. Defaults to "Local Virtuoso".
    • Returns query results as a JSONL string.
  • podbc_spasql_query

    • Execute a SPASQL (SQL/SPARQL hybrid) query return results. This is a Virtuoso-specific feature.
    • Input parameters:
      • query (string, required): The SPASQL query string.
      • max_rows (number, optional): Maximum number of rows to return. Defaults to 20.
      • timeout (number, optional): Query timeout in milliseconds. Defaults to 30000.
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • dsn (string, optional): ODBC data source name. Defaults to "Local Virtuoso".
    • Returns the result from the underlying stored procedure call (e.g., Demo.demo.execute_spasql_query).
  • podbc_sparql_query

    • Execute a SPARQL query and return results. This is a Virtuoso-specific feature.
    • Input parameters:
      • query (string, required): The SPARQL query string.
      • format (string, optional): Desired result format. Defaults to 'json'.
      • timeout (number, optional): Query timeout in milliseconds. Defaults to 30000.
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • dsn (string, optional): ODBC data source name. Defaults to "Local Virtuoso".
    • Returns the result from the underlying function call (e.g., "UB".dba."sparqlQuery").
  • podbc_virtuoso_support_ai

    • Utilizes a Virtuoso-specific AI Assistant function, passing a prompt and optional API key. This is a Virtuoso-specific feature.
    • Input parameters:
      • prompt (string, required): The prompt text for the AI function.
      • api_key (string, optional): API key for the AI service. Defaults to "none".
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • dsn (string, optional): ODBC data source name. Defaults to "Local Virtuoso".
    • Returns the result from the AI Support Assistant function call (e.g., DEMO.DBA.OAI_VIRTUOSO_SUPPORT_AI).

Troubleshooting

For easier troubleshooting:

  1. Install the MCP Inspector:

    npm install -g @modelcontextprotocol/inspector
  2. Start the inspector:

    npx @modelcontextprotocol/inspector uv --directory /path/to/mcp-sqlalchemy-server run mcp-sqlalchemy-server

Access the provided URL to troubleshoot server interactions.

mcp-sqlalchemy-server FAQ

How do I connect mcp-sqlalchemy-server to my database?
Configure the server with your database's ODBC connection string compatible with SQLAlchemy providers.
Can mcp-sqlalchemy-server execute stored procedures?
Yes, it supports executing stored procedures, especially on Virtuoso DBMS.
What output formats does the server support for query results?
It supports JSONL for structured data and markdown tables for readable output.
Is mcp-sqlalchemy-server limited to Virtuoso DBMS?
No, it works with any DBMS that has a SQLAlchemy provider and supports ODBC.
How does mcp-sqlalchemy-server expose database schema information?
It provides endpoints to fetch schemas, tables, and detailed table descriptions including keys and nullable attributes.
What technologies is mcp-sqlalchemy-server built on?
It uses FastAPI for the web server, pyodbc for ODBC connectivity, and SQLAlchemy for ORM and database abstraction.
Can I use mcp-sqlalchemy-server to integrate with LLMs like OpenAI, Claude, or Gemini?
Yes, it exposes structured database context that can be consumed by LLMs via MCP for enhanced data-driven workflows.
How do I deploy mcp-sqlalchemy-server?
Deploy it as a FastAPI application with access to your ODBC data sources and configure MCP clients to connect.