Matillion (Cloud Data Integration & ELT) Connector for AI agents.
6 live capabilities
Manage enterprise ELT pipelines and cloud data warehouse connections.
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Why people use Matillion (Cloud Data Integration & ELT)
Matillion for Auditing Enterprise ELT Workflows
With this Connector, you just ask your agent. You get a direct summary of successes, failures, and active agents in one message. It turns a multi-minute search into a three-second conversation.
What Vinkius changes
You get a conversational interface for your entire Matillion data infrastructure.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Identifying failed pipeline errors
A data engineer needs to know why a 'Sales-Sync' job failed.
- Real-world use case 02
Auditing cloud warehouse connections
An analytics lead wants to see what warehouses are connected.
- Real-world use case 03
Monitoring agent health
A BI operator needs to check for active agents.
Complete set · 6capabilities
The complete Matillion (Cloud Data Integration & ELT) capability set.
These are the exact actions your AI can choose when you ask it to work with Matillion (Cloud Data Integration & ELT).
01—03
3 capabilities in this set.
Part of 6 available through Matillion (Cloud Data Integration & ELT).
- 01 Capability
Get pipeline
Pull specific details about a single pipeline. Use this to inspect the logic of a specific transformation.
- 02 Capability
List executions
View the history of recent pipeline runs. It's the fastest way to see what succeeded or failed recently.
- 03 Capability
List environments
Check all your configured destination environments. This ensures your data is mapping correctly to Snowflake or BigQuery.
04—06
3 capabilities in this set.
Part of 6 available through Matillion (Cloud Data Integration & ELT).
- 04 Capability
List agents
Find all active Matillion runtime agents. Use this to verify which components are physically resolving operations.
- 05 Capability
List projects
Browse your project containers in the Matillion Hub. This helps you navigate the broad organization of your data work.
- 06 Capability
List pipelines
See every ETL pipeline in your account. This helps you get a quick overview of your data flows.
Set up in minutes
One URL. Then ask Matillion (Cloud Data Integration & ELT) to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Matillion (Cloud Data Integration & ELT) from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_cvCobHBQ94OGYTB46AOSlQ9YTUsvJ3NLbXMZS4ld/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Matillion (Cloud Data Integration & ELT), and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Matillion (Cloud Data Integration & ELT) for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_cvCobHBQ94OGYTB46AOSlQ9YTUsvJ3NLbXMZS4ld/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Matillion (Cloud Data Integration & ELT) URL.
- Step 03
Save and start
Save the connection and enable Matillion (Cloud Data Integration & ELT) in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"matillion-cloud-data-integration-elt": {
"url": "https://edge.vinkius.com/vk_preview_cvCobHBQ94OGYTB46AOSlQ9YTUsvJ3NLbXMZS4ld/mcp"
}
}
} - Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Matillion (Cloud Data Integration & ELT)
Open Agent mode in chat and ask: "Using Matillion (Cloud Data Integration & ELT), help me...". 6 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"matillion-cloud-data-integration-elt": {
"url": "https://edge.vinkius.com/vk_preview_cvCobHBQ94OGYTB46AOSlQ9YTUsvJ3NLbXMZS4ld/mcp"
}
}
} - Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Matillion (Cloud Data Integration & ELT)
Ask Copilot: "Using Matillion (Cloud Data Integration & ELT), help me...". 6 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"matillion-cloud-data-integration-elt": {
"url": "https://edge.vinkius.com/vk_preview_cvCobHBQ94OGYTB46AOSlQ9YTUsvJ3NLbXMZS4ld/mcp"
}
}
} - Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Matillion (Cloud Data Integration & ELT)
Open Cascade and ask: "Using Matillion (Cloud Data Integration & ELT), help me...". 6 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"matillion-cloud-data-integration-elt": {
"url": "https://edge.vinkius.com/vk_preview_cvCobHBQ94OGYTB46AOSlQ9YTUsvJ3NLbXMZS4ld/mcp"
}
}
} - Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Matillion (Cloud Data Integration & ELT)
Ask Cline: "Using Matillion (Cloud Data Integration & ELT), help me...". 6 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add matillion-cloud-data-integration-elt --transport http "https://edge.vinkius.com/vk_preview_cvCobHBQ94OGYTB46AOSlQ9YTUsvJ3NLbXMZS4ld/mcp" - Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Matillion (Cloud Data Integration & ELT)
Ask Claude: "Using Matillion (Cloud Data Integration & ELT), show me...". 6 tools are ready
Where the request belongs
Work Matillion can move forward.
For the data engineer who's tired of manually hunting through logs at 2am or the analytics lead who needs a quick status check on production pipelines without logging into the full hub.
Data Engineer
Audits pipeline designs and checks execution logs during deployment cycles to catch errors early.
Analytics Lead
Monitors project health and warehouse environment statuses from a single workspace without switching apps.
BI Operations Team
Tracks active runtime agents to ensure high availability of critical ELT processes efficiently.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse ConnectorsPortable.io
Manage your Portable ETL pipelines directly via your AI agent. monitor flows, sync runs, and destination details seamlessly.
Integrate.io (ETL & Data Integration)
Manage data pipelines via Integrate.io. list pipelines, monitor job runs, and audit data transformations.
Hevo Data (ETL & Data Pipeline)
Manage data pipelines via Hevo. list pipelines, monitor destinations, and track usage.
Fivetran
Manage data movement via Fivetran. monitor connectors and destinations, handle groups, track sync states, and audit users directly from any AI agent.
Data Pipeline Prover
A data team asked an AI to build an ETL pipeline. No schema contract. No idempotency. No freshness SLA. The pipeline ran for 3 months. silently inserting 2.4 million duplicate records and serving stale data to dashboards nobody questioned. This capability forces schema validation at boundaries, idempotent writes, freshness alerting, and end-to-end lineage tracing.
Hightouch (Reverse ETL)
Synchronize data via Hightouch. list syncs, monitor runs, and manage data models.
Bring your own AI
Change the model, client or framework. Keep Matillion connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Matillion.
The practical details behind the request, access and result.
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 capability 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 capability 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 capability 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.
One connection away
Give your agent a direct line to Matillion.
Connect Matillion once. Keep it beside 5,900+ managed Connectors when the next task needs more.
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