Teradata

official

A collection of tools for managing the platform, addressing data quality and reading and writing to Teradata Database.

GitHub

What can you do with Teradata MCP?

Query and analyze data — Ask natural-language questions to explore tables, profile data, and visualize patterns without writing SQL.
Generate semantic layers — Create custom domain-specific tools, prompts, and cubes from YAML definitions via the customization guide.
Run AI and RAG pipelines — Perform semantic search, retrieval-augmented generation, and vector storage using the rag, tdvs, and fs tools.
Manage database administration — Handle security, monitor capacity, and automate backups through the dba, sec, and bar tool suites.
Execute long-running analytics — Launch tdml_* analytic functions as background tasks and poll for results instead of blocking.
Protect against destructive actions — Use Guard Mode for multi-step confirmation flows on bar_* and sec_* operations.

Documentation

Teradata MCP Server

Connect AI agents directly to Teradata with enterprise security and extensibility.

Teradata MCP Server architecture

Quick Start (Choose Your Path)

Client	Best For	Setup Time
Claude Desktop	Exploratory analysis, platform admin	5 min
VS Code + Copilot	Data engineering, agent development	5 min
Open WebUI	Testing new LLMs locally	5 min
Code Examples	Build your own client	varies
Flowise	Visual agent builder	10 min

Pre-requisites: Teradata database (or free sandbox) + uv

Claude Desktop Setup (No Installation)

Add this to claude_desktop_config.json (Settings > Developer > Edit Config):

{
  "mcpServers": {
    "teradata": {
      "command": "uvx",
      "args": ["teradata-mcp-server"],
      "env": {
        "DATABASE_URI": "teradata://<USERNAME>:<PASSWORD>@<HOST_URL>:1025/<USERNAME>"
      }
    }
  }
}

What You Can Do

Use Case	Capabilities	Tools
Query & Analyze	Explore tables, profile data, explain results, visualize patterns—no SQL needed	base, dba, qlty, plot
Semantic Layer	Generate custom semantic layers and tools from YAML or with our Agent Skill	Learn more →
AI & RAG Pipelines	Semantic search, retrieval-augmented generation, vector storage	rag, tdvs, fs
Database Admin	Manage security, monitor capacity, automate backups	dba, sec, bar

What's New (Latest Release)

FastMCP v4 — Sessionless protocol, background tasks for long-running analytics, argument completion
Response Caching — 5-minute TTL signals reduce redundant database queries in multi-turn conversations
Guard Mode — Multi-step confirmation flows for destructive operations (bar_, sec_)
Background Tasks — tdml_* analytic functions return task IDs for polling instead of blocking
Argument Completion — Auto-suggest table and column names from schema as users type
Hooks Capability — Intercept tool calls for custom monitoring, audit, or rate-limiting
Row Limit Protection — Configurable caps (DEFAULT_ROW_LIMIT, MAX_ROW_LIMIT) prevent LLM token overflow
Enhanced Security — VX views for fine-grained row-level access control

Extend & Deploy

Add Custom Logic
Use hooks to intercept tool calls for monitoring, audit trails, or validation → Hooks Guide

Define Semantic Layers
Create domain-specific tools, prompts, and cubes in YAML → Customization Guide

Deploy Everywhere
Run as CLI (uv), HTTP server, Docker container, or cloud service → Installation Guide

See It In Action

Voice Agent — Real-time bidirectional audio with Amazon Nova Sonic
Web Agent — Interactive chat UI with Google ADK framework
Flowise Builder — Visual drag-and-drop workflows
Custom Middleware — Performance monitoring patterns

Learn More

Full Documentation — Installation, configuration, architecture, security
Video Tutorials — Step-by-step walkthroughs
Developer Guide — Extend and contribute
Architecture — How components work together

Contributing

We welcome contributions! See our Contributing Guide and Developer Guide to get started.