Airbyte MCP. Audit your data pipelines with conversational prompts.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Airbyte MCP lets your agent talk to your data pipelines. Audit ETL/ELT jobs by checking sync history, listing every source (like Postgres or Stripe), and auditing all connections—all without touching a dashboard.
Get immediate status on your entire data stack.
What your AI agents can do
Get connection
Retrieves specific details for one defined Airbyte sync connection.
Get source
Gets detailed information about a single data source configured in Airbyte.
List connections
Lists every active sync connection established within your airbyte instance.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
Airbyte MCP: 7 Tools for Pipeline Monitoring
These tools let you programmatically manage and inspect every aspect of your Airbyte environment, from job history to source configuration.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Airbyte on Vinkius019d754aget connection
Retrieves specific details for one defined Airbyte sync connection.
019d754aget source
Gets detailed information about a single data source configured in Airbyte.
019d754alist connections
Lists every active sync connection established within your airbyte instance.
019d754alist destinations
Provides a full list of all defined data warehouse destinations.
019d754alist jobs
Shows historical synchronization runs, including success rates and failure reasons for a connection.
019d754alist sources
Lists all active data origins (like Postgres or Stripe) configured in the workspace.
019d754alist workspaces
Returns a list of all airbyte workspaces and their general configuration settings.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Airbyte, then connect any of our 4,800+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,800+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Airbyte. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
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Policy on every call
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 7 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Checking Data Status Means Clicking Through Too Many Tabs
Today, checking your data pipelines means logging into the dashboard. You jump to 'Connections,' then you have to open a specific connection's page just to see its job history. If you need to check ten different connections, you repeat those steps ten times, risking human error every single time.
With this MCP, that process vanishes. You ask your agent to audit the status of multiple jobs in one prompt, using tools like `list_jobs`. The agent aggregates all that data and gives you a clean answer right where you're working.
Airbyte MCP: Get Connection Status with Simple Prompts
The manual steps of finding the correct workspace, navigating to the specific connection ID, and then drilling down into job logs are gone. You just need the name or a general scope.
Now you can verify connectivity status across your entire stack with one prompt, using `list_connections` and related tools. It's direct.
What you can do with this MCP connector
Managing modern data stacks means constantly watching Airbyte dashboards for failures. It’s exhausting. This MCP connects your airbyte instance to your agent so you can audit your pipelines conversationally. Instead of clicking through seven different tabs to figure out what went wrong, you just ask. You can get a full list of active connections or verify if the nightly sync job failed by calling list_jobs.
It’s like having an expert data operations analyst sitting next to you. If you're using Vinkius for your MCP catalog, this connection lets you keep all your monitoring tools centralized in one spot. You can check which sources are feeding data or verify the status of entire workspaces with simple prompts.
019d754a-987d-72d0-8004-b3bb6a4d7810 
How Airbyte MCP Works
- 1 Subscribe to this MCP, providing your Airbyte API URL and API Key.
- 2 Your agent calls the necessary tool functions (e.g.,
list_connections) through your preferred AI client. - 3 The tool retrieves the data from Airbyte's API and returns a structured report for your agent to interpret.
The bottom line is, you use your agent to run diagnostic queries against Airbyte without writing any code or navigating complex UIs.
Who Is Airbyte MCP For?
This MCP is for the data engineer who needs to debug a failing pipeline at 2 AM. It's for the analytics team member who needs an instant inventory of all configured data paths, and anyone tired of staring at complex dashboard UIs.
Debugging a failed ETL run by checking list_jobs to find out if the issue was credential-related or source-specific.
Quickly generating an inventory of all configured warehouse destinations using list_destinations before building a new data model.
Getting a high-level overview of every active source feeding the main data lake by calling list_sources.
What Changes When You Connect
- Stop manually checking dashboards. Your agent uses
list_jobsto immediately tell you if the nightly run failed and why. - Get a complete picture of your infrastructure using
list_connections, giving you an instant topology map without clicking through multiple sections. - Inventory all data sources instantly. Calling
list_sourcesgives you a clean list of every origin, whether it's Postgres or Stripe. - Verify where your data lands. Use
list_destinationsto see every single target warehouse—Snowflake, BigQuery, etc.—in one go. - Know your scope with
list_workspaces. This tool shows you which environments and workspaces are active in the account. - Pinpoint problems fast. You can use
get_connectionorget_sourceto pull detailed UUID configs when debugging a specific component.
Real-World Use Cases
Investigating a Broken Data Feed
A data analyst notices the Snowflake table is empty. Instead of logging into Airbyte, they prompt their agent to check list_jobs for that specific connection ID. The agent replies: 'The job failed at 03:00 AM; credentials expired.' Problem solved in seconds.
Auditing a New Project Setup
An analytics engineer is starting a new project and needs to know which data sources are available. They prompt the agent to run list_sources and get a clean list of all available databases, skipping manual UI navigation.
Checking Data Flow Compliance
A platform admin must prove that only approved destinations receive data. They ask their agent to execute list_destinations, which returns an authoritative list, proving compliance without human error.
The Tradeoffs
Manual Dashboard Review
When a sync fails, you open the Airbyte UI. You click 'Jobs,' then filter by date range, then scroll through logs looking for the specific connection ID.
→
Just ask your agent to run list_jobs and give it the target connection ID. The tool handles the filtering and reporting immediately.
Assuming Source Availability
A developer starts writing a script assuming a necessary source like 'Oracle' is available, only to find out later that the actual list was different.
→
Always run list_sources first. This confirms exactly what data origins exist before you write any integration logic.
Ignoring Workspace Scope
Trying to monitor a job in one environment while failing to realize that the connection was set up in another, isolated workspace.
→
Start by calling list_workspaces to verify you're looking at the right scope before trying any specific monitoring tools.
When It Fits, When It Doesn't
Use this MCP if your primary pain point is operational visibility into data movement. If you need to know 'Did X happen, and why?' across various sources (Postgres, Stripe) and destinations (Snowflake, BigQuery), this tool is perfect. You'll use list_jobs, list_connections, and get_source together.
Don't use this if you need to manage the underlying data in the warehouse itself; for that, you need a dedicated query execution MCP. Also, don't rely on it for user management or billing—those tools are outside of Airbyte's scope. This is purely about pipeline status and inventory.
Common Questions About Airbyte MCP
Does this work with Airbyte Cloud and Self-Hosted Enterprise instances? +
Yes. You are required to pass the URL parameter during setup. You can use 'https://api.airbyte.com/v1' for Airbyte Cloud, or point it directly to your private self-hosted API endpoint hostname.
Can the agent create new connections or trigger sync jobs automatically? +
Currently, this core MCP exposes read-only tools designed to safely list, track, and monitor your infrastructure without accidentally mutating mission-critical data warehouse state during conversational usage.
How do I find a specific Connection ID to check its jobs? +
Simply ask the agent to run the list connections tool first! It will output all active connections alongside their UUIDs, which you can then ask the agent to dive deeper into.
When I use `get_source`, what specific schema information does my agent receive about a data origin? +
The agent returns detailed metadata, including the source's UUID and supported column types. This lets you verify if the source has all the necessary fields before checking its sync job history.
If I run `list_connections`, how do I filter to see only connections that are currently paused or disabled? +
The tool lists every configured connection. To check the active status, your agent retrieves the full details using get_connection for each item, allowing you to identify dormant pipelines.
If I suspect my API credentials are bad, does `get_connection` help me troubleshoot? +
It confirms the current status of the connection without needing manual updates. If the retrieved data points to an authentication error or outdated UUID, you know exactly where to focus your fix.
How can I ensure my agent is monitoring the correct environment using `list_workspaces`? +
This tool lists all available workspace IDs. Use this first step to confirm which operational context your data pipelines belong to before running any job status checks.
What happens if I run too many commands, like multiple `list_sources` calls in quick succession? +
The MCP handles Airbyte's API rate limits. Your agent monitors the usage and will automatically signal a temporary block or retry when it detects that your query quota has been hit.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.