# Alation MCP for AI Agents MCP

> Alation MCP brings enterprise data governance directly to your AI agent. Use this connector to search, audit, and query complex data assets across massive catalogs using plain conversation. It lets you discover metadata, trace lineage, and retrieve schema details without writing a single SQL command.

## Overview
- **Category:** brain-trust
- **Price:** Free
- **Tags:** data-catalog, data-governance, metadata-management, data-discovery, sql-querying, data-intelligence

## Description

Working with large data environments means spending way too much time just trying to find the right data set or figuring out who owns it. This MCP changes that by connecting your AI agent directly to your Alation instance. You can ask natural language questions—like, 'Show me all tables related to Q3 sales figures'—and the system handles the complexity for you.

It lets you go beyond simple searches. Your agent can audit table schemas, trace data lineage back to its source, and even pull saved queries from Alation Compose. Everything is exposed through a clean chat interface managed by Vinkius. You get enterprise-grade data intelligence without needing specialized SQL knowledge or navigating dozens of dashboards.

## Tools

### search_catalog
Searches your entire catalog for specific data assets using keywords.

### list_data_sources
Retrieves a list of all available data sources within the catalog.

### list_schemas
Lists all schemas contained within a specific data source.

### list_tables
Displays all tables associated with a selected schema.

### list_columns
Provides an inventory of columns for a specified table.

### get_object_metadata
Pulls detailed metadata, including descriptions and stewards, for any object in the catalog.

### list_saved_queries
Shows a list of previously saved SQL queries stored in the system.

### get_query_results
Fetches cached results from executed SQL queries, so you don't have to re-run them.

### list_custom_fields
Lists and audits custom governance fields applied across the catalog objects.

### get_lineage
Maps out data lineage, showing how a table is populated from its source systems.

## Prompt Examples

**Prompt:** 
```
I need to know which systems feed into the 'Global Sales' dashboard.
```

**Response:** 
```
**Lineage Report: Global Sales Dashboard**

This dashboard relies on three primary data feeds:

*   `Sales_Transactions`: Primary source, last updated 2026-06-12.
*   `Regional_Adjustments`: Used for currency conversion.
*   `Product_Master`: Provides current product taxonomy.

**Next Steps:** Would you like me to audit the governance metadata for any of these three sources?
```

**Prompt:** 
```
Show me all tables that contain customer PII and are marked as sensitive.
```

**Response:** 
```
**Sensitive Data Audit Results**

The following 4 tables were found matching both 'PII' keywords and the 'Sensitive' custom governance tag:

| Table Name | Schema | Steward | Last Audited |
| :--- | :--- | :--- | :--- |
| `customer_master` | Prod | Alice K. | 2026-05-01 |
| `user_login_history` | Audit | Bob L. | 2026-06-10 |
| `billing_details` | Finance | Carol R. | N/A |

*Note: The 'billing_details' table requires an immediate steward assignment.*
```

**Prompt:** 
```
List the saved queries and pull the results for the one that checks user signups.
```

**Response:** 
```
**Query Retrieval Report**

Found 12 saved SQL items. Here are your recent ones:

*   `Monthly Churn Report` (Last run: yesterday)
*   `Revenue by Region` (Last run: week ago)
*   `Active User Audit` (Saved for Signups):

**Cached Results for 'Active User Audit':**
```json
[{"date": "2026-06-11", "count": 1450}, {"date": "2026-06-12", "count": 1610}]
```
*The results show a steady growth in active users.*
```

## Capabilities

### Search the Data Catalog
You can search across all your catalog data sources using keywords and advanced filters to locate relevant schemas, tables, and data assets.

### Inspect Object Metadata
Retrieve detailed information about any data object, including its official description, assigned data steward, or specific governance tags.

### Trace Data Lineage
Follow the path of your data. This capability shows exactly where a table originated and which downstream dashboards or systems rely on it.

### Audit Governance Fields
List and examine custom governance fields attached to catalog objects, helping you ensure compliance details are properly filled out.

### Query Saved SQL Results
List saved SQL queries and retrieve cached execution results from Alation Compose so you don't have to run the same report twice.

## Use Cases

### A new analyst needs a report on customer churn rates.
Instead of asking a domain expert for the right table name, the agent uses `search_catalog` and identifies 'Customer Metrics'. The analyst then runs `get_lineage` to confirm that this dataset comes from the approved source system before building their dashboard.

### The compliance team needs to prove data residency.
They instruct their agent to use `list_custom_fields` across all tables in the 'Production' schema. The agent audits every object, verifying that the required 'Jurisdiction Tag' field has been populated everywhere.

### An engineer is modifying a core reporting dashboard.
They use the agent to run `get_lineage` on the key metric table. The output immediately warns them that three critical downstream dashboards ('Global Sales', 'Finance Forecast') depend on this data, preventing a major outage.

### A BI lead wants to reuse last quarter's complex financial analysis.
Rather than recreating the query manually, they ask the agent to `list_saved_queries`. They find 'Q2 Revenue by Region', and with one prompt, retrieve its cached results using `get_query_results`.

## Benefits

- Stop guessing where data lives. Use the `search_catalog` tool to instantly pinpoint schemas, tables, or entire sources using natural language prompts.
- Eliminate manual metadata checks. With `get_object_metadata`, you can ask your agent for stewardship details and definitions on demand, ensuring compliance right away.
- Understand data trust immediately. The `get_lineage` tool maps out the complete journey of any dataset, showing exactly what feeds into it or depends on it.
- Save time running reports. You can use `list_saved_queries` to see past work and `get_query_results` to retrieve cached output without re-execution.
- Maintain governance integrity by using the `list_custom_fields` tool, allowing you to audit specific compliance details attached to every data object.

## How It Works

The bottom line is you talk to your AI client naturally, and it does the heavy lifting of querying and interpreting your complex data catalog structure.

1. First, subscribe to this MCP on Vinkius. You'll need your specific Alation Instance URL and an API Access Token.
2. Next, connect your preferred AI client (like Cursor or Claude) using the credentials you entered. This links your agent to the entire Alation catalog.
3. Finally, just ask your agent a question—for example, 'What is the lineage for the Customer ID table?' The MCP uses its tools to pull the data and present the answer in conversation.

## Frequently Asked Questions

**How does the Alation MCP help me find data I need for reporting?**
It turns searching into conversation. Instead of sifting through endless UI menus, you ask your agent what you need (e.g., 'sales figures') and it uses its tools to pinpoint all relevant tables and sources in the catalog.

**Can I use Alation MCP to check if my data is compliant?**
Yes. You can audit metadata completion by listing custom fields or getting object details, letting you confirm that required governance tags are applied before publishing reports.

**What if I need to know where a specific column of data came from?**
You use the lineage tool. It traces the entire journey of that single column, showing every source table and system it passed through—it’s like seeing the full pedigree.

**Does Alation MCP save me time running reports?**
Yes. You can list saved SQL queries and retrieve cached results. This means if you ran a complex report yesterday, you don't have to re-run the query; your agent just pulls the old numbers for you.

**Is Alation MCP only for data engineers?**
No. While it’s powerful for engineers, analysts use it constantly. You can search and audit metadata simply using natural conversation, making complex governance tasks accessible to everyone.