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MCP Server ODBC via PyODBC

@MCP-Mirror

Repository

Basic information

Category

Other

License

MIT license

Transports

stdio

Author

MCP-Mirror

About MCP Server ODBC via PyODBC

Mirror of

MCP Server ODBC via PyODBC config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "OpenLinkSoftware_mcp-pyodbc-server": {
      "command": "npx",
      "args": [
        "@modelcontextprotocol/inspector",
        "uv",
        "--directory",
        "/path/to/mcp-pyodbc-server",
        "run",
        "mcp-pyodbc-server"
      ]
    }
  }
}

MCP Server ODBC via PyODBC tools

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Fetch the live tool list by running this server in a temporary sandbox using the button above.

Overview

What is MCP Server ODBC via PyODBC?

A lightweight MCP (Model Context Protocol) server built with FastAPI and pyodbc that enables AI agents to interact with ODBC-compatible databases. It is compatible with Virtuoso DBMS and other DBMS backends that have an ODBC driver.

How to use MCP Server ODBC via PyODBC?

Clone the repository, set environment variables (ODBC_DSN, ODBC_USER, ODBC_PASSWORD, API_KEY) in a .env file, and configure an MCP client like Claude Desktop by adding a claude_desktop_config.json entry with the command uv --directory /path/to/mcp-pyodbc-server run mcp-pyodbc-server and the required environment variables.

Key features of MCP Server ODBC via PyODBC

  • List all schema names from the connected database.
  • Retrieve table information for a specific schema.
  • Describe table columns, data types, keys, and nullability.
  • Filter tables by name substring.
  • Execute SQL queries returning results in JSONL or Markdown format.
  • Execute Virtuoso-specific SPASQL and SPARQL queries.

Use cases of MCP Server ODBC via PyODBC

  • Exploring database schemas and tables for data discovery.
  • Generating structured descriptions of table structures for AI agents.
  • Running ad-hoc SQL queries and receiving formatted results.
  • Integrating with Virtuoso DBMS for SPARQL/SPASQL queries.
  • Leveraging the Virtuoso AI Support Assistant for LLM interactions.

Frequently asked questions

1

What are the runtime dependencies?

Requires Python with `uv`, the `unixODBC` runtime, and an installed ODBC driver for the target database. An ODBC DSN must be configured in `~/.odbc.ini`.

2

How does the server authenticate?

Authentication is handled via an environment variable `API_KEY` set by the client (e.g., in `claude_desktop_config.json`).

3

Does it work with databases other than Virtuoso?

Yes. The core ODBC functions (get schemas, tables, describe table, execute queries) work with any database that has an ODBC driver. Virtuoso-specific tools (SPASQL/SPARQL, AI Assistant) only apply to Virtuoso.

4

Where does the data live?

The server does not store data; it connects to a remote database via ODBC using the configured DSN.

5

What transport does the server use?

The server runs as a subprocess managed by the MCP client (e.g., Claude Desktop) over stdio, as configured in `claude_desktop_config.json`.

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