Metaplane MCP. Manage Data Quality and Incidents via Chat
Metaplane connects data observability directly into your AI client. Get full control over data quality by tracking monitors, incident history, and system health through natural conversation. You can check connection schemas, list all active alerts, or trigger a manual monitor run without leaving your chat interface.
Give Claude and any AI agent real-world access
List existing monitors or fetch detailed health metrics and metadata for specific monitoring points.
Pull real-time details on data quality incidents, including historical records and resolution status.
Programmatically start a monitor run to validate data quality immediately, regardless of the schedule.
View all connected databases, warehouses, and schemas to build a map of your company's data lineage.
List and examine configured alert rules to ensure your team gets notified when things go wrong.
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What AI agents can do with Metaplane MCP with 10 Tools
These tools let you read account info, list incidents or monitors, view connections, and manually trigger checks for complete data visibility.
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 Metaplane MCPGet Account Info
Retrieves general account information for your Metaplane setup.
Get Incident
Fetches detailed records and status updates for one specific data quality incident.
Get Monitor
Gets comprehensive details about a single configured data monitor.
Get Monitor Runs
Retrieves the execution history and results for a specific data monitor.
List Configured Alerts
Lists all active notification settings and alert rules configured in Metaplane.
List Data Connections
Enumerates every connected data source, warehouse, and database within your account.
List Incidents
Generates a list of historical or active data incidents across the entire system.
List Monitors
Provides an overview and list of every configured data monitor currently set up.
List Connection Schemas
Lists all available schemas within a specified data connection or warehouse.
Trigger Monitor Run
Manually initiates a monitor run to check the current data quality against defined...
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
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 each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Metaplane, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
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Data health status is spread across five different web tabs.
Today, checking your data quality requires a multi-tab session. You jump to the Monitor tab to see if things are running; then you open the Incident dashboard to check for alerts; next, you click on connection details just to verify schemas; and finally, you scroll through run history logs to find the root cause of an anomaly.
With this MCP, your agent handles all that clicking. You ask it to list all data monitors, see if there are active incidents, and even check connected databases—all in one conversation. It collapses a 10-minute manual audit into seconds.
Get full visibility using Metaplane's tools.
You no longer need to remember which tool tracks what. You can use `list_monitors` to see every check configured, then ask your agent to list connection schemas across the affected data source, and finally run `get_monitor_runs` to prove when it last passed.
The process shifts from investigation (clicking tabs) to inquiry (asking questions). The state of your entire data platform is now available via natural language prompts.
What Metaplane MCP does for your AI
This MCP lets you manage data quality and understand the status of your pipelines using only conversation. Instead of logging into Metaplane's dashboard and clicking through multiple tabs to see if everything's running okay, you just ask your AI client. You can pull a list of all configured monitors or fetch details on a specific incident that popped up last night.
Need to validate data quality right now? Your agent triggers a monitor run for you. Furthermore, you can view the connection schemas across different databases and even check active alert rules. When you connect this through Vinkius, your AI client becomes your single pane of glass for all things data observability.
019d75d3-869f-7334-9a90-0f6125786560 How to set up Metaplane MCP
The bottom line is that you manage complex data health checks using simple chat prompts instead of navigating multiple web dashboards.
Subscribe to the Metaplane MCP using your API key.
Connect this MCP via Vinkius to any AI client (like Cursor or Claude).
Ask your agent natural language questions, like 'What were the top three incidents yesterday?' and get immediate data answers.
Who uses Metaplane MCP
Data engineers, platform reliability teams, and BI analysts need this. It's for the ops engineer who's tired of clicking through dozens of dashboard tabs at 2 am just to find out which pipeline broke last night.
Uses the MCP to list connected schemas and trigger monitor runs when they suspect a data pipeline failure, validating quality on demand.
Checks incident history and fetches details for specific incidents to quickly triage alerts without manual dashboard access.
Lists all data monitors and reviews alert configurations to understand what metrics are being tracked across the company's datasets.
Benefits of connecting Metaplane MCP
Stop jumping between dashboards. You can list all monitors or check specific incident details directly through your AI client, keeping context in one place.
Validate data quality on demand. Instead of waiting for a scheduled run, you use the trigger_monitor_run tool to manually test data integrity immediately after an ETL job.
Understand your entire stack. The MCP lets you list all data connections and schemas, giving you full visibility into where your data comes from.
Proactive monitoring is simple. You can list configured alerts or get details on a specific monitor to ensure the right rules are running.
Contextualized troubleshooting. When an incident happens, you can run list_incidents and then drill down with get_incident without leaving your chat window.
Metaplane MCP use cases
Investigating a sudden dashboard dip
A data analyst notices revenue numbers are off. Instead of filing a ticket, they ask their agent to list all monitored connections and schemas for the affected reports. This reveals that the primary Snowflake warehouse connection was listed as disconnected, pinpointing the failure point immediately.
Pre-release data validation
A data engineer finishes an ETL pipeline and needs to confirm quality before deployment. They use their agent to trigger_monitor_run on the key tables, validating that row counts and null checks pass instantly, saving a manual QA cycle.
Reviewing historical system failures
An SRE is prepping for an audit. They ask their agent to list all data incidents over the last quarter. This quickly surfaces recurring high-severity issues that might require architectural fixes, rather than just patching code.
Auditing pipeline dependencies
A BI architect needs to know which datasets feed into a critical dashboard. They use the MCP to list all data connections and connection schemas, mapping out every dependency in minutes using simple prompts.
Metaplane MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Treating it like a general query tool
Asking 'What is my data observability?' The agent will give vague marketing answers because the prompt lacks specific actions.
Instead, ask for concrete data: 'List all configured alerts' or 'Show me the run history for the Postgres Row Count monitor'. Use tools like list_configured_alerts to get actionable status.
Ignoring connection scope
Trying to find a schema without knowing which database it belongs to, resulting in a vague list of all possible schemas.
First use list_data_connections to identify the correct source. Then ask for the specific data structures using list_connection_schemas for precision.
Manually checking every status
Logging into the web UI and clicking through monitors, incidents, runs, and connections one by one until all are verified.
Ask your agent to perform a bulk check: 'List all data monitors' followed by 'list_incidents'. This aggregates the necessary status updates instantly.
When to use Metaplane MCP
Use this MCP if your primary pain point is siloed visibility. If you currently have multiple dashboards—one for incidents, one for monitor health, and another for connection schemas—you need this. It centralizes that data into conversation. However, don't use it if you simply need to write a SQL query or perform ad-hoc data transformations; this MCP is about observability and reporting on state, not execution of raw code. If your goal is pure ETL development, you might prefer a dedicated CI/CD tool instead. But if the goal is 'Did my pipeline break? And what's happening right now?' then Metaplane is exactly what you need.
Frequently asked questions about Metaplane MCP
How do I use the Metaplane MCP to check if a specific monitor failed? +
You can first run list_monitors to find the monitor ID, and then use get_monitor for detailed status. If it failed recently, you should also check list_incidents.
Can Metaplane MCP list all my databases? +
Yes. You can run the list_data_connections tool to enumerate every data source connected to your account.
What is the difference between listing monitors and triggering a monitor run with Metaplane MCP? +
Listing monitors (list_monitors) shows you what checks are configured. Triggering a run (trigger_monitor_run) actually executes those checks right now to validate current data quality.
Does the Metaplane MCP help me find which schemas exist? +
Yes, it does. You can use list_connection_schemas after identifying a specific connection to see all available structures within that warehouse.