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teradata-mcp-server

by Teradata

Overview

This server provides a Model Context Protocol (MCP) interface for interacting with Teradata databases, offering tools for database administration, data quality, SQL optimization, feature store management, RAG (Retrieval Augmented Generation) workflows, vector store operations, plotting, and backup/restore, often used to enable AI agents or LLMs to perform database-related tasks.

Installation

Run Command
uvx teradata-mcp-server --database_uri "teradata://USERNAME:PASSWORD@HOST:1025/DATABASE" --mcp_transport streamable-http --mcp_host 0.0.0.0 --mcp_port 8001

Environment Variables

  • DATABASE_URI
  • DSA_BASE_URL
  • DSA_USERNAME
  • DSA_PASSWORD
  • TD_VS_BASE_URL

Security Notes

The server has critical SQL Injection vulnerabilities. Many tools construct SQL queries using f-strings with user-controlled input (e.g., `table_name`, `database_name`, `column_name`, `user_name`, `obj_name`) directly embedded into the SQL string without proper escaping or parameter binding. For example, `handle_base_tableDDL` executes `show table {table_name}` and `handle_dba_tableSqlList` uses `LIKE '%{table_name}%'`, which can be exploited to execute arbitrary SQL commands. Additionally, default credentials ('admin'/'admin') are used for DSA API access if environment variables are not set, posing a risk in non-development environments. The server listens on `0.0.0.0` by default in Docker, making it externally accessible. While `eval` is used in `resolve_type_hint`, it is within a restricted namespace and context, reducing its immediate danger compared to the SQL injection issues.

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Stats

Interest Score43
Security Score1
Cost ClassHigh
Avg Tokens5000
Stars32
Forks46
Last Update2025-11-22

Tags

TeradataMCP ServerDatabase ManagementData QualitySQL OptimizationAI AgentsRAGVector StoreFeature StoreBackup/RestorePythonPerformance Testing