Hevo Data (ETL & Data Pipeline) Connector for AI agents.
6 live capabilities
Manage your ETL pipelines and warehouse destinations through a conversational interface.
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Why people use Hevo Data (ETL & Data Pipeline)
Hevo Data for Monitoring ETL Pipeline Health
With this Connector, you just ask your agent. You get a quick status update on your pipelines and destinations in one go. It turns a five-minute search into a five-second conversation.
What Vinkius changes
You get a conversational interface for your entire Hevo 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
Troubleshooting a failed sync
A data engineer asks the agent to check the status of a specific pipeline to see why data isn't hitting Snowflake.
- Real-world use case 02
Pre-reporting audit
An analytics lead asks the agent to list all transformation models to ensure the staging logic is ready for the weekly report.
- Real-world use case 03
Budget monitoring
An ops manager asks the agent for a usage report to see how many rows were replicated this month.
Complete set · 6capabilities
The complete Hevo Data (ETL & Data Pipeline) capability set.
These are the exact actions your AI can choose when you ask it to work with Hevo Data (ETL & Data Pipeline).
01—03
3 capabilities in this set.
Part of 6 available through Hevo Data (ETL & Data Pipeline).
- 01 Capability
List pipelines
See every ETL pipeline in your Hevo account. This helps you get a bird's-eye view of your data flows.
- 02 Capability
Get pipeline
Pull specific details for a single pipeline. Use this to check exact routing and frequency for a specific ID.
- 03 Capability
List destinations
See all your warehouse targets like BigQuery or Snowflake. This is great for verifying where data is being sent.
04—06
3 capabilities in this set.
Part of 6 available through Hevo Data (ETL & Data Pipeline).
- 04 Capability
List models
Review all your transformation models. It helps you ensure your staging logic remains consistent.
- 05 Capability
List workflows
View the DAG workflows connecting your transformations. This shows how your data moves across the stack.
- 06 Capability
Get usage
Check your current row counts and billing limits. It's the easiest way to stay on top of your account health.
Set up in minutes
One URL. Then ask Hevo Data (ETL & Data Pipeline) to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Hevo Data (ETL & Data Pipeline) 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_g8OahZ0tlknHo4zGlDARjBa11ENx2y9HNf6P2vgT/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 Hevo Data (ETL & Data Pipeline), and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Hevo Data (ETL & Data Pipeline) for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_g8OahZ0tlknHo4zGlDARjBa11ENx2y9HNf6P2vgT/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 Hevo Data (ETL & Data Pipeline) URL.
- Step 03
Save and start
Save the connection and enable Hevo Data (ETL & Data Pipeline) in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"hevo-data-etl-data-pipeline": {
"url": "https://edge.vinkius.com/vk_preview_g8OahZ0tlknHo4zGlDARjBa11ENx2y9HNf6P2vgT/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 Hevo Data (ETL & Data Pipeline)
Open Agent mode in chat and ask: "Using Hevo Data (ETL & Data Pipeline), help me...". 6 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"hevo-data-etl-data-pipeline": {
"url": "https://edge.vinkius.com/vk_preview_g8OahZ0tlknHo4zGlDARjBa11ENx2y9HNf6P2vgT/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 Hevo Data (ETL & Data Pipeline)
Ask Copilot: "Using Hevo Data (ETL & Data Pipeline), help me...". 6 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"hevo-data-etl-data-pipeline": {
"url": "https://edge.vinkius.com/vk_preview_g8OahZ0tlknHo4zGlDARjBa11ENx2y9HNf6P2vgT/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 Hevo Data (ETL & Data Pipeline)
Open Cascade and ask: "Using Hevo Data (ETL & Data Pipeline), help me...". 6 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"hevo-data-etl-data-pipeline": {
"url": "https://edge.vinkius.com/vk_preview_g8OahZ0tlknHo4zGlDARjBa11ENx2y9HNf6P2vgT/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 Hevo Data (ETL & Data Pipeline)
Ask Cline: "Using Hevo Data (ETL & Data Pipeline), help me...". 6 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add hevo-data-etl-data-pipeline --transport http "https://edge.vinkius.com/vk_preview_g8OahZ0tlknHo4zGlDARjBa11ENx2y9HNf6P2vgT/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 Hevo Data (ETL & Data Pipeline)
Ask Claude: "Using Hevo Data (ETL & Data Pipeline), show me...". 6 tools are ready
Where the request belongs
Work Hevo Data can move forward.
This is for the data pro who's tired of manual dashboard hopping. It's for the person who needs to know why a sync failed at 3 AM without having to log into three different consoles to find the answer.
Data Engineer
Checking pipeline health and replication statuses during a production deployment.
Analytics Lead
Verifying that transformation models are correct before a big board meeting.
Ops Manager
Monitoring row usage and billing ceilings to keep the department under budget.
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.
Fivetran
Manage data movement via Fivetran. monitor connectors and destinations, handle groups, track sync states, and audit users directly from any AI agent.
Matillion (Cloud Data Integration & ELT)
Manage data pipelines via Matillion. audit ETL workflows, track execution statuses, and monitor cloud environments.
Stitch Data
Automate data pipelines via Stitch. manage sources, destinations, and push data directly to your warehouse from any AI agent.
Airbyte
Monitor your Airbyte data pipelines via AI. track sync jobs, list sources, and check connections instantly.
Bring your own AI
Change the model, client or framework. Keep Hevo Data 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 Hevo Data.
The practical details behind the request, access and result.
Can the Hevo Data MCP help me check if my data is reaching Snowflake?
Yes, you can ask your agent to list your destinations. It will show you the status of all warehouse targets, including Snowflake, BigQuery, and Redshift.
How do I see my row usage limits using the Hevo Data MCP?
Just ask your agent for your usage metrics. It will pull your current row counts and billing ceilings in real-time so you can stay on budget.
Can I see all my ETL pipelines at once with this Connector?
Yes, your agent can pull a full list of all your active pipelines, including their IDs and current statuses, in one command.
Does the Hevo Data MCP work for BigQuery and Redshift?
Yes, it supports monitoring for multiple warehouse destinations, including BigQuery and Redshift, alongside Snowflake.
Can I use this to check my transformation models?
Yes, you can ask your agent to list your models to verify that your staging logic and mappings are correct.
Can I check the status of my data destinations through my agent?
Yes. Use the list_destinations capability to see all your warehouse targets. Your agent will provide the status and details of where your data is being replicated, ensuring delivery to platforms like BigQuery or Snowflake.
How do I find a specific pipeline's configuration?
Use the get_pipeline capability with a unique Pipeline ID to extract explicit routing mappings and ingestion frequencies. This is perfect for auditing specific ETL flows without manual searching.
Can I monitor my account's row usage through a conversation?
Absolutely. The get_usage capability retrieves real-time account usage metrics and billing ceilings, helping you track how many rows have been replicated and ensure you stay within your plan's limits.
One connection away
Give your agent a direct line to Hevo Data.
Connect Hevo Data once. Keep it beside 5,900+ managed Connectors when the next task needs more.
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