# Matillion MCP for AI Agents AI Agent Connect

> Matillion MCP lets you manage your data pipelines and ELT workflows through an AI agent. You can audit execution statuses, monitor cloud environments like Snowflake or BigQuery, and inspect project metadata without leaving your chat interface. It turns complex data orchestration into a simple conversation. Use it to keep a pulse on your entire data lifecycle and get straight answers about your infrastructure.

## Overview
- **Category:** brain-trust
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_cvCobHBQ94OGYTB46AOSlQ9YTUsvJ3NLbXMZS4ld/ai-agent-connect
- **Tags:** elt-pipelines, data-integration, workflow-orchestration, data-transformation, cloud-data-warehouse

## Description

Managing enterprise data pipelines usually means jumping between browser tabs, searching through project folders, and hunting for failed execution logs. It's tedious work that pulls you away from actual data analysis. This Connector changes that by bringing your Matillion Data Productivity Cloud directly into your AI agent. Instead of navigating a complex dashboard, you just ask your agent to tell you which pipelines are running or why a specific job failed. You can check your Snowflake or Redshift connections, list your active runtime agents, and peek into the structural components of your data transformations. It makes it way easier to keep a pulse on your entire data lifecycle. Because Vinkius hosts this Connector, you can connect it to your existing workflow in seconds. You get a way to audit your infrastructure and manage project containers without the friction of manual navigation. It's about moving from clicking through menus to getting straight answers about your data flow.

## Tools

### get_pipeline
Pull specific details about a single pipeline. Use this to inspect the logic of a specific transformation.

### list_executions
View the history of recent pipeline runs. It's the fastest way to see what succeeded or failed recently.

### list_environments
Check all your configured destination environments. This ensures your data is mapping correctly to Snowflake or BigQuery.

### list_agents
Find all active Matillion runtime agents. Use this to verify which components are physically resolving operations.

### list_projects
Browse your project containers in the Matillion Hub. This helps you navigate the broad organization of your data work.

### list_pipelines
See every ETL pipeline in your account. This helps you get a quick overview of your data flows.

## Prompt Examples

**Prompt:** 
```
Show me the status of the last 5 runs for my data pipelines.
```

**Response:** 
```
I've checked the recent history for you. Here are the last 5 executions:

| Pipeline Name | Status | Timestamp |
| :--- | :--- | :--- |
| **Inventory_Load** | ✅ Success | 10:45 AM |
| **Marketing_Sync** | 🔄 Running | 10:50 AM |
| **Web_Log_Ingestion** | ❌ Failed | 10:52 AM |
| **Sales_Sync** | ✅ Success | 10:55 AM |
| **Finance_Batch** | ✅ Success | 11:00 AM |

The 'Web_Log_Ingestion' job failed; would you like me to look at the error?
```

**Prompt:** 
```
What cloud environments do I have set up in Matillion?
```

**Response:** 
```
You have 3 destination environments configured:

*   **Snowflake-Prod** (Targeting: SF_WH_01)
*   **Redshift-Staging** (Targeting: AWS_NODE_ALPHA)
*   **BigQuery-Analytics** (Targeting: GCP_DATASET_V1)

I can pull the project mappings for these if you need them.
```

**Prompt:** 
```
List all the pipelines in my project.
```

**Response:** 
```
I found the following ETL pipelines in your current project:

*   Sales-Data-Sync (ID: pipe-123)
*   Customer-360-View (ID: pipe-456)
*   Finance-Consolidation (ID: pipe-789)

Which one would you like to see the details for?
```

## Capabilities

### List all managed ETL pipelines
See every data pipeline in your account in one go.

### Get specific pipeline details
Retrieve structural components and logic for a specific pipeline.

### View recent pipeline executions
Check the success or failure status of your latest runs.

### List cloud destination environments
See all configured targets like Snowflake, Redshift, or BigQuery.

### See active runtime agents
Identify which components are physically resolving operations.

### Browse project containers
Navigate the broad organization of your pipelines and environments.

## Use Cases

### Identifying failed pipeline errors
A data engineer needs to know why a 'Sales-Sync' job failed. They ask the agent to show the last 5 executions and the agent identifies a specific error in the logs.

### Auditing cloud warehouse connections
An analytics lead wants to see what warehouses are connected. They ask the agent to list environments and get a summary of all Snowflake and BigQuery targets.

### Monitoring agent health
A BI operator needs to check for active agents. They ask the agent to list runtime agents to ensure the hybrid SaaS components are healthy.

### Navigating project scope
A project manager wants to see the scope of a new project. They ask the agent to list projects and then pull the specific pipelines within a container.

## Benefits

- Faster troubleshooting: Use list_executions to quickly identify failed jobs and find the exact error without digging through nested menus.
- Better visibility: Get a clear view of your entire infrastructure by using list_agents to see what's running on your local network.
- Accurate mapping: Use list_environments to verify that your data is hitting the right Snowflake or Redshift targets every time.
- Easier navigation: Quickly jump between project containers using list_projects to keep your team's work organized and accessible.
- Detailed inspection: Use get_pipeline to pull structural components and schema mappings directly into your chat for quick review.

## How It Works

The bottom line is you get a conversational interface for your entire Matillion data infrastructure.

1. Subscribe to the Connector and provide your Matillion API URL, Client ID, and Client Secret.
2. Connect the Connector to your preferred client like Claude, Cursor, or Windsurf.
3. Ask your agent to check pipeline statuses, list environments, or audit execution logs.

## Frequently Asked Questions

**Can the Matillion MCP help me find failed jobs?**
Yes, it lets you see recent execution statuses so you can identify failed deployments and bottlenecks immediately without navigating the hub.

**Does the Matillion MCP work with Snowflake or BigQuery?**
It allows you to list and audit the destination environments connected to those cloud data warehouses to ensure your data is mapping correctly.

**Can I use the Matillion MCP to see my runtime agents?**
You can enumerate all active Matillion runtime agents to monitor your local network operations and ensure high availability of your processes.

**How does the Matillion MCP help with data engineering?**
It lets you audit pipeline designs and retrieve structural components directly in your chat, making it faster to review data transformations.

**Can I see my project containers using the Matillion MCP?**
Yes, it can navigate your broad project containers to help you organize and find your pipelines more efficiently.

**What information can I get about a specific pipeline?**
You can retrieve the underlying orchestration definitions and schema mappings for any specific pipeline ID to get a deep-dive into the logic.

**Can I see the status of recent ELT pipeline executions through my agent?**
Yes. Use the `list_executions` tool to retrieve the audit trail of recent Matillion workflows. Your agent will report which pipelines succeeded, which failed, and provide the operational context for each run.

**How do I check which cloud data warehouse environments are configured?**
The `list_environments` tool extracts the destination structures attached to your account. Your agent will list environments pointing to Snowflake, Redshift, or BigQuery, helping you verify your data distribution endpoints.

**Can my agent track the health of active Matillion runtime agents?**
Absolutely. Use the `list_agents` tool to monitor active Hybrid SaaS agents. Your agent will report which runtime components are currently resolving operations across your network, ensuring your data productivity is uninterrupted.