Teradata MCP Server

An MCP (Model Context Protocol) server for Teradata. Enables Claude (via Cowork or Claude Desktop) to run SQL queries, explore metadata, and interact directly with Teradata databases.

Features

• Execute arbitrary SQL queries with configurable row limits

• List tables and views within a database

• Preview sample rows from any table

• Test connectivity and retrieve the database version

• Environment-based configuration via .env

• Supports stdio transport (Claude Desktop / Cowork) and streamable-http

Related MCP server: Informix MCP Server

Tools

Details

ping() Confirms the connection is active. Useful for validating configuration before running queries.

read_query(sql, row_limit?) Executes any SQL statement. row_limit is optional — defaults to DEFAULT_ROW_LIMIT (1000). Never exceeds MAX_ROW_LIMIT (50000). Returns truncated: true when results were cut off.

list_tables(database) Queries DBC.TablesV and returns the name, type (Table / View), and creation date of each object in the given database.

table_preview(database, table, row_limit?) Executes SELECT TOP N * FROM database.table. Default row_limit is 10.

Installation

Prerequisites

• Python 3.11+

• uv (package manager)

• Access to a Teradata server

Steps

# 1. Clone the repository
git clone <repository-url>
cd teradata-mcp-server

# 2. Install dependencies
uv sync

# 3. Set up environment variables
cp .env.example .env
# Edit .env with your Teradata credentials

# 4. Test the connection
uv run teradata-mcp-server

Configuration

Environment variables (.env)

Cowork Configuration

In Claude Cowork (or Claude Desktop), go to Settings → Claude Cowork → Edit Config and add the block below inside mcpServers:

{
  "mcpServers": {
    "teradata": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/teradata-mcp-server",
        "run",
        "teradata-mcp-server"
      ],
      "env": {
        "DATABASE_URI": "teradata://user:password@host:1025/database"
      }
    }
  }
}

Replace /path/to/teradata-mcp-server with the absolute path to the project on your machine and fill in your credentials in DATABASE_URI.

If you prefer to keep credentials in .env rather than exposing them in the config JSON, omit the "env" field — the server reads .env automatically on startup.

Project Structure

teradata-mcp-server/
├── .env.example                  # Environment variables template
├── pyproject.toml                # Dependencies and entry point (uv/hatchling)
├── README.md
└── src/
    ├── core/
    │   ├── __init__.py
    │   ├── config.py             # Settings (pydantic-settings, reads .env)
    │   └── connection.py         # SQLAlchemy singleton engine (get_engine)
    ├── tools/
    │   ├── __init__.py
    │   └── base.py               # Tools: ping, read_query, list_tables, table_preview
    └── server/
        ├── __init__.py
        └── teradata_mcp_server.py  # Entry point: FastMCP instance + mcp.run()