How to Use the Checkly MCP in Cline

Q: Can Cline automatically fix a failing Checkly monitor?

Yes. Cline uses getcheckdetails to read the failure logs, edits the local file causing the error, and calls triggercheckrun to confirm the fix works.

Q: Can Cline check my Checkly alert channels using MCP?

Yes. Cline uses the listchecklyalertchannels tool to inspect where your notifications are sent, helping you verify your team gets alerted during outages.

Q: Can I view historical latency trends?

Yes. Cline calls getcheckperformancemetrics to pull response times and error rates over time, allowing the agent to write a summary of your API health.

Let Cline inspect Checkly performance metrics, run instant API tests, and write fixes for broken endpoints in VS Code.

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Connect Checkly MCP to Cline

Create your Vinkius account to connect Checkly to Cline and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Checkly with Cline

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Auto-remediate broken endpoints with Cline

The `get_check_details` tool exposes failing assertions and response payloads directly to Cline. The agent analyzes the stack trace, locates the offending controller file in VS Code, and edits the code to resolve the issue. Because Cline operates autonomously, it does not just tell you what is wrong. It runs `list_checkly_checks` to identify the broken endpoint, edits the code, and verifies the fix before you even commit.

Verify live deployments using this MCP Server

The `trigger_check_run` tool lets Cline run live API and browser checks on demand to test your changes. You do not need to push to staging or wait for CI to see if your local changes broke production monitors. Cline triggers the check, monitors the execution, and pulls performance data using `get_check_performance_metrics`. If the latency spikes, Cline flags the regression immediately.

Audit alerts and cron monitors

The `list_checkly_alert_channels` tool pulls your active notification targets so Cline can audit your alerting setup. The agent checks if your Slack or PagerDuty channels are properly configured for critical endpoints. Cline also uses `list_checkly_heartbeats` and `list_check_groups` to ensure all background jobs are monitored. It points out missing cron monitors and suggests new heartbeat checks based on your local codebase.

Setup guide

Set up Checkly MCP in Cline

Prerequisites

VS Code with Cline extension installed
Active Vinkius subscription with a valid endpoint token

1

Open Cline MCP settings

Click the Cline icon in the VS Code sidebar to open the Cline panel. Then click the MCP Servers icon (server stack) at the top-right corner of the panel.
2

Add a remote server

Click "Remote Servers" at the top, then click "Add Remote MCP". In the Name field, type checkly-mcp. In the URL field, paste your Vinkius endpoint: https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp. Get your token from cloud.vinkius.com.
3

Enable the server

After saving, the server appears in the Cline MCP panel. Toggle the switch to enable it. The status indicator turns green when the connection is live.
4

Start using tools

Return to the Cline chat and ask: "Check my latest Checkly refund status." Cline will discover the available tools and request your approval before invoking each one — giving you full control over every action.

Cline MCP Settings

{
  "mcpServers": {
    "checkly-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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Common questions about Checkly MCP in Cline

Yes. Cline uses `get_check_details` to read the failure logs, edits the local file causing the error, and calls `trigger_check_run` to confirm the fix works.

Open the Cline sidebar, click the MCP icon, and add the server via the Remote Servers tab. It connects instantly using our secure transport.

Yes. Cline uses the `list_checkly_alert_channels` tool to inspect where your notifications are sent, helping you verify your team gets alerted during outages.

Yes. Cline calls `get_check_performance_metrics` to pull response times and error rates over time, allowing the agent to write a summary of your API health.

Your performance metrics and check details are processed inside an ephemeral, zero-trust MCP container. The data is only used to answer your current prompt and is never stored or used for training.

Use it with your favorite AI tools

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