Connect to Databases via SQLAlchemy and PyODBC
An MCP server for ODBC databases via SQLAlchemy/pyodbc - schema/table introspection and SQL, SPASQL, or SPARQL queries, Virtuoso-optimized.
Why it matters
Enable seamless access to various ODBC-compliant databases, including Virtuoso, PostgreSQL, MySQL, and SQLite, by leveraging SQLAlchemy and PyODBC. This asset allows for structured data retrieval and execution of SQL queries.
Outcomes
What it gets done
Retrieve database schemas and table structures.
Execute SQL, SPASQL, and SPARQL queries against connected databases.
Fetch query results in JSONL or Markdown table formats.
Manage database credentials securely through environment variables.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/vb-openlink-generic-sqlalchemy-object-relational-database-connectivity-for-pyodbc | bash Capabilities
Tools your agent gets
Get a list of database schemas available for the connected DBMS
Get a list of tables associated with the selected database schema
Provide table description including column names, data types, and constraints
Get a list of tables matching a substring pattern in the selected schema
Execute a SQL query and return results in JSONL format
Execute a SQL query and return results in JSONL format
Execute a SQL query and return results in Markdown table format
Execute a SPASQL query and return results
Overview
OpenLink Generic SQLAlchemy Object-Relational Database Connectivity for PyODBC MCP Server
An MCP server exposing ODBC schema and table introspection plus SQL, SPASQL, and SPARQL query execution via pyodbc and SQLAlchemy, optimized for Virtuoso DBMS. Use when an AI assistant needs to introspect schemas and tables or run SQL, SPASQL, or SPARQL queries against an ODBC-connected database.
What it does
A lightweight MCP server, built with FastAPI, pyodbc, and SQLAlchemy, that connects an AI assistant to any ODBC-reachable database - Virtuoso, PostgreSQL, MySQL, SQLite, or another backend with a SQLAlchemy provider - over a single configured ODBC DSN. It exposes schema and table introspection (list schemas, list tables, describe a table's columns, data types, nullability, and primary/foreign keys), substring-based table search, general SQL query execution with a choice of JSON, Markdown-table, or JSON Lines output, and, for Virtuoso specifically, stored-procedure execution plus its SPASQL/SPARQL hybrid query support and a database-side AI assistant function callable from inside the same connection.
When to use - and when NOT to
Use it when an AI assistant needs to introspect schemas and tables, or run SQL, SPASQL, or SPARQL queries against an ODBC-connected database. Setup requires the uv package manager, a working unixODBC runtime, checked via odbcinst -j for config locations and odbcinst -q -s for available DSNs, and an ODBC DSN configured in ~/.odbc.ini pointing at the target database - a Virtuoso example:
[VOS]
Description = OpenLink Virtuoso
Driver = /path/to/virtodbcu_r.so
Database = Demo
Address = localhost:1111
WideAsUTF16 = Yes
The SQLAlchemy connection URL format varies by backend: virtuoso+pyodbc://user:password@VOS for Virtuoso, standard postgresql://, mysql+pymysql://, and sqlite:/// URLs for PostgreSQL, MySQL, and SQLite respectively, all tested against this server. For troubleshooting, the MCP Inspector can be installed and pointed at the server's own uv run invocation to interactively debug tool calls and see exactly what each one returns before wiring it into a real conversation.
Capabilities
Schema and table introspection covers listing, substring filtering, and detailed description, giving an agent enough structural context about an unfamiliar database to write correct queries without guessing at column names or foreign key relationships first. Standard SQL queries come back in three interchangeable output formats depending on what the caller actually needs next: plain JSON for programmatic consumption, a Markdown table for direct display to a person, or JSON Lines for streaming or line-oriented processing of larger result sets. The three Virtuoso-specific query tools extend past ordinary SQL entirely - a hybrid SQL-and-SPARQL query language for combining relational and graph-style querying in one statement, a pure graph-query language for triple-store style data, and a database-side AI assistant function that can be invoked with a natural-language prompt from inside the same connection, rather than requiring a completely separate AI integration layer bolted on top of the database.
How to install
Clone the repository, set ODBC_DSN, ODBC_USER, ODBC_PASSWORD, and API_KEY in .env, then add the server to Claude Desktop's config pointing uv run mcp-sqlalchemy-server at the cloned directory with the same environment variables.
Who it's for
Developers connecting an AI assistant to a Virtuoso, PostgreSQL, MySQL, SQLite, or other ODBC-reachable database who need schema introspection and flexible query execution, including Virtuoso's own SPASQL/SPARQL hybrid and AI features where applicable, and who would rather have three interchangeable output formats for a query result than a single fixed shape their downstream tooling has to adapt to every time.
Source README
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
Install uv:
pip install uvOr use Homebrew:
brew install uvunixODBC Runtime Environment Checks:
Check installation configuration (i.e., location of key INI files) by running:
odbcinst -jList available data source names by running:
odbcinst -q -sODBC 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 = YesSQLAlchemy 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:
Install the MCP Inspector:
npm install -g @modelcontextprotocol/inspectorStart the inspector:
npx @modelcontextprotocol/inspector uv --directory /path/to/mcp-sqlalchemy-server run mcp-sqlalchemy-server
Access the provided URL to troubleshoot server interactions.
FAQ
Common questions
Discussion
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